Studies¶
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pyEX.studies.technicals.cycle.
ht_dcperiod
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Hilbert Transform - Dominant Cycle Period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.cycle.
ht_dcphase
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Hilbert Transform - Dominant Cycle Phase for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.cycle.
ht_phasor
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Hilbert Transform - Phasor Components for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.cycle.
ht_sine
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Hilbert Transform - SineWave for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.cycle.
ht_trendmode
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Hilbert Transform - Trend vs Cycle Mode for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
acos
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric ACos for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
add
(client, symbol, timeframe='6m', col1='open', col2='close')[source]¶ This will return a dataframe of Vector Arithmetic Add for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col1 (string) –
- col2 (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
asin
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric ASin for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
atan
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric ATan for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
ceil
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Ceil for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
cos
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric Cos for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
cosh
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric Cosh for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
div
(client, symbol, timeframe='6m', col1='open', col2='close')[source]¶ This will return a dataframe of Vector Arithmetic Div for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col1 (string) –
- col2 (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
exp
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Arithmetic Exp for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
floor
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Floor for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
ln
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Log Natural for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
log10
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Log10 for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
max
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Highest value over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
maxindex
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Highest value over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
min
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Lowest value over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
minindex
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Lowest value over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
minmax
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Lowest and highest values over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
minmaxindex
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Indexes of lowest and highest values over a specified period for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
mult
(client, symbol, timeframe='6m', col1='open', col2='close')[source]¶ This will return a dataframe of Vector Arithmetic Add for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col1 (string) –
- col2 (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
sin
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric SIN for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
sinh
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric Sinh for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
sqrt
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Square Root for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
sub
(client, symbol, timeframe='6m', col1='open', col2='close')[source]¶ This will return a dataframe of Vector Arithmetic Add for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col1 (string) –
- col2 (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
sum
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ This will return a dataframe of Summation for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
tan
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric Tan for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.math.
tanh
(client, symbol, timeframe='6m', col='close')[source]¶ This will return a dataframe of Vector Trigonometric Tanh for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
adx
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of average directional movement index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
adxr
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of average directional movement index rating for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
apo
(client, symbol, timeframe='6m', col='close', fastperiod=12, slowperiod=26, matype=0)[source]¶ This will return a dataframe of Absolute Price Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- fastperiod (int) – fast period to calculate across
- slowperiod (int) – slow period to calculate across
- matype (int) – moving average type (0-sma)
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
aroon
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of Aroon for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
aroonosc
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of Aroon Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
bop
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', volumecol='volume')[source]¶ This will return a dataframe of Balance of power for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- volumecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
cci
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of Commodity Channel Index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
cmo
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Chande Momentum Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
dx
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of Directional Movement Index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
macd
(client, symbol, timeframe='6m', col='close', fastperiod=12, slowperiod=26, signalperiod=9)[source]¶ This will return a dataframe of Moving Average Convergence/Divergence for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- fastperiod (int) – fast period to calculate across
- slowperiod (int) – slow period to calculate across
- signalperiod (int) – macd signal period
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
macdext
(client, symbol, timeframe='6m', col='close', fastperiod=12, fastmatype=0, slowperiod=26, slowmatype=0, signalperiod=9, signalmatype=0)[source]¶ This will return a dataframe of Moving Average Convergence/Divergence for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- fastperiod (int) – fast period to calculate across
- fastmatype (int) – moving average type (0-sma)
- slowperiod (int) – slow period to calculate across
- slowmatype (int) – moving average type (0-sma)
- signalperiod (int) – macd signal period
- signalmatype (int) – moving average type (0-sma)
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
mfi
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', volumecol='volume', period=14)[source]¶ This will return a dataframe of Money Flow Index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
minus_di
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of Minus Directional Indicator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
minus_dm
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of Minus Directional Movement for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
mom
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Momentum for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
plus_di
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of Plus Directional Movement for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
plus_dm
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of Plus Directional Movement for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
ppo
(client, symbol, timeframe='6m', col='close', fastperiod=12, slowperiod=26, matype=0)[source]¶ This will return a dataframe of Percentage Price Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- fastperiod (int) – fast period to calculate across
- slowperiod (int) – slow period to calculate across
- matype (int) – moving average type (0-sma)
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
roc
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Rate of change: ((price/prevPrice)-1)*100 for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
rocp
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Rate of change Percentage: (price-prevPrice)/prevPrice for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
rocr
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Rate of change ratio: (price/prevPrice) for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
rocr100
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Rate of change ratio 100 scale: (price/prevPrice)*100 for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
rsi
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of Relative Strength Index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
stoch
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)[source]¶ This will return a dataframe of Stochastic for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- fastk_period (int) – fastk_period
- slowk_period (int) – slowk_period
- slowk_matype (int) – slowk_matype
- slowd_period (int) – slowd_period
- slowd_matype (int) – slowd_matype
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.momentum.
stochf
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', fastk_period=5, slowk_period=3, slowk_matype=0, slowd_period=3, slowd_matype=0)[source]¶ This will return a dataframe of Stochastic Fast for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- fastk_period (int) – fastk_period
- slowk_period (int) – slowk_period
- slowk_matype (int) – slowk_matype
- slowd_period (int) – slowd_period
- slowd_matype (int) – slowd_matype
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
stochrsi
(client, symbol, timeframe='6m', closecol='close', period=14, fastk_period=5, fastd_period=3, fastd_matype=0)[source]¶ This will return a dataframe of Stochastic Relative Strength Index for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
- fastk_period (int) – fastk_period
- fastd_period (int) – fastd_period
- fastd_matype (int) – moving average type (0-sma)
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
trix
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ This will return a dataframe of 1-day Rate-Of-Change(ROC) of a Triple Smooth EMA for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- col (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
ultosc
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period1=7, period2=14, period3=28)[source]¶ This will return a dataframe of Ultimate Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period1 (int) – period to calculate across
- period2 (int) – period to calculate across
- period3 (int) – period to calculate across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.momentum.
willr
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of Williams’ % R for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – period to calculate across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
bollinger
(client, symbol, timeframe='6m', col='close', period=2)[source]¶ This will return a dataframe of bollinger bands for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
dema
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of double exponential moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
ema
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of exponential moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
ht_trendline
(client, symbol, timeframe='6m', col='close')[source]¶ - This will return a dataframe of hilbert trendline
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
kama
(client, symbol, timeframe='6m', col='close', period=30)[source]¶ - This will return a dataframe of kaufman adaptive moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
mama
(client, symbol, timeframe='6m', col='close', fastlimit=0, slowlimit=0)[source]¶ - This will return a dataframe of mesa adaptive moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- fastlimit (int) –
- slowlimit (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
mavp
(client, symbol, timeframe='6m', col='close', periods=None, minperiod=2, maxperiod=30, matype=0)[source]¶ - This will return a dataframe of moving average with variable period
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
- minperiod (int) –
- maxperiod (int) –
- matype (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
midpice
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ - This will return a dataframe of midprice over period
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
midpoint
(client, symbol, timeframe='6m', col='close', period=14)[source]¶ - This will return a dataframe of midpoint over period
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- period (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
sar
(client, symbol, timeframe='6m', highcol='high', lowcol='low', acceleration=0, maximum=0)[source]¶ - This will return a dataframe of parabolic sar
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- highcol (string) –
- lowcol (string) –
- acceleration (int) –
- maximum (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
sarext
(client, symbol, timeframe='6m', highcol='high', lowcol='low', startvalue=0, offsetonreverse=0, accelerationinitlong=0, accelerationlong=0, accelerationmaxlong=0, accelerationinitshort=0, accelerationshort=0, accelerationmaxshort=0)[source]¶ - This will return a dataframe of parabolic sar extended
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- highcol (string) –
- lowcol (string) –
- startvalue (int) –
- offsetonreverse (int) –
- accelerationinitlong (int) –
- accelerationlong (int) –
- accelerationmaxlong (int) –
- accelerationinitshort (int) –
- accelerationshort (int) –
- accelerationmaxshort (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
sma
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of exponential moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
t3
(client, symbol, timeframe='6m', col='close', periods=None, vfactor=0)[source]¶ - This will return a dataframe of tripple exponential moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
- vfactor (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
tema
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of triple exponential moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
trima
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of triangular moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.overlap.
wma
(client, symbol, timeframe='6m', col='close', periods=None)[source]¶ - This will return a dataframe of weighted moving average
- for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
- col (string) –
- periods (int) –
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl2crows
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of Two crows for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3blackcrows
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 black crows for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3inside
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 inside up/down for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3linestrike
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 line strike for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3outside
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 outside for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3starsinsouth
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 stars in south for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdl3whitesoldiers
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of 3 white soldiers for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlabandonedbaby
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of abandoned baby for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdladvanceblock
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of advance block for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlbelthold
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of belt hold for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlbreakaway
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of breakaway for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlclosingmarubozu
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of closing maru bozu for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlconcealbabyswallow
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of conceal baby swallow for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlcounterattack
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of counterattack for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdldarkcloudcover
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of dark cloud cover for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdldoji
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of doji for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdldojistar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of doji star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdldragonflydoji
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of dragonfly doji for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlengulfing
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of engulfing for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdleveningdojistar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of evening doji star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdleveningstar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of evening star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlgapsidesidewhite
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of up.down-gap side-by-side white lines for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlgravestonedoji
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of gravestone doji for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhammer
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of hammer for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhangingman
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of hanging man for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlharami
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of harami for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlharamicross
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of harami cross for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhighwave
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of high-wave candle for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhikkake
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of hikkake pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhikkakemod
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of modified hikkake pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlhomingpigeon
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of homing pigeon for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlidentical3crows
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of identical three crows for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlinneck
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of in-neck pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlinvertedhammer
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of inverted hammer for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlkicking
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of kicking for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlkickingbylength
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of kicking bull/bear determing by the longer marubozu for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlladderbottom
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of ladder bottom for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdllongleggeddoji
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of long legged doji for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdllongline
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of long line candle for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlmarubozu
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of marubozu for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlmatchinglow
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of matching low for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlmathold
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of mat hold for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlmorningdojistar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of morning doji star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlmorningstar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close', penetration=0)[source]¶ This will return a dataframe of morning star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- penetration (int) – penetration
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlonneck
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of on-neck pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlpiercing
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of piercing pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlrickshawman
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of rickshaw man for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlrisefall3methods
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of rising/falling three methods for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlseparatinglines
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of separating lines for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlshootingstar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of shooting star for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlshortline
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of short line candle for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlspinningtop
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of spinning top for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlstalledpattern
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of stalled pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlsticksandwich
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of stick sandwich for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdltakuri
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of takuri dragonfly doji with very long lower shadow for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdltasukigap
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of tasuki gap for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlthrusting
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of thrusting pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdltristar
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of tristar pattern for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlunique3river
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of unique 3 river for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlupsidegap2crows
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of upside gap two crows for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.pattern.
cdlxsidegap3methods
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of upside/downside gap three methods for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.price.
avgprice
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of average price for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- opencol (string) – column to use to calculate
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.price.
medprice
(client, symbol, timeframe='6m', highcol='high', lowcol='low')[source]¶ This will return a dataframe of median price for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.price.
typprice
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of typical price for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.price.
wclprice
(client, symbol, timeframe='6m', opencol='open', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of weighted close price for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
beta
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of beta for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
correl
(client, symbol, timeframe='6m', highcol='high', lowcol='low', period=14)[source]¶ This will return a dataframe of Pearson’s Correlation Coefficient(r) for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
linearreg
(client, symbol, timeframe='6m', closecol='close', period=14)[source]¶ This will return a dataframe of linear regression for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
linearreg_angle
(client, symbol, timeframe='6m', closecol='close', period=14)[source]¶ This will return a dataframe of linear regression angle for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
linearreg_intercept
(client, symbol, timeframe='6m', closecol='close', period=14)[source]¶ This will return a dataframe of linear regression intercept for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
-
pyEX.studies.technicals.statistic.
linearreg_slope
(client, symbol, timeframe='6m', closecol='close', period=14)[source]¶ This will return a dataframe of linear regression slope for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.statistic.
stddev
(client, symbol, timeframe='6m', closecol='close', period=14, nbdev=1)[source]¶ This will return a dataframe of standard deviation for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
- nbdev (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.statistic.
tsf
(client, symbol, timeframe='6m', closecol='close', period=14, nbdev=1)[source]¶ This will return a dataframe of standard deviation for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.statistic.
var
(client, symbol, timeframe='6m', closecol='close', period=14, nbdev=1)[source]¶ This will return a dataframe of var for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- period (int) – period to calculate adx across
- nbdev (int) –
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volatility.
atr
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of average true range for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – time period to calculate over
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volatility.
natr
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', period=14)[source]¶ This will return a dataframe of normalized average true range for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- period (int) – time period to calculate over
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volatility.
trange
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close')[source]¶ This will return a dataframe of true range for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volume.
ad
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', volumecol='volume')[source]¶ This will return a dataframe of Chaikin A/D Line for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- volumecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volume.
adosc
(client, symbol, timeframe='6m', highcol='high', lowcol='low', closecol='close', volumecol='volume', fastperiod=3, slowperiod=10)[source]¶ This will return a dataframe of Chaikin A/D Oscillator for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- highcol (string) – column to use to calculate
- lowcol (string) – column to use to calculate
- closecol (string) – column to use to calculate
- volumecol (string) – column to use to calculate
- fastperiod (int) – fast period to calculate across
- slowperiod (int) – slow period to calculate across
Returns: result
Return type: DataFrame
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pyEX.studies.technicals.volume.
obv
(client, symbol, timeframe='6m', closecol='close', volumecol='volume')[source]¶ This will return a dataframe of On Balance Volume for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) – Client
- symbol (string) – Ticker
- timeframe (string) – timeframe to use, for pyEX.chart
- closecol (string) – column to use to calculate
- volumecol (string) – column to use to calculate
Returns: result
Return type: DataFrame
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pyEX.studies.peercorrelation.
peerCorrelation
(client, symbol, timeframe='6m')[source]¶ This will return a dataframe of peer correlations for the given symbol across the given timeframe
Parameters: - client (pyEX.Client) –
- symbol (string) –
- timeframe (string) –
Returns: result
Return type: DataFrame