Pandas Basics

Review the Pandas documentation, if not proficient, and more specifically the following concepts of Series and DataFrames and DataFrame Extensions.

What is a Pandas Series and DataFrame?

Pandas Series
Pandas DataFrame
Pandas DataFrame Extension

Series vs DataFrame Column Count

A Pandas Series returns a single column.
A Pandas DataFrame returns multiple column.

Properties#

The "ta" extension has some optional properties that may be of use when using ohlcv data.

adjusted#

Get/Set the adjusted_close column.

Mode:

Get: The adjusted column as str.
Set: The column name, to set as the adjusted column. Default: None

config#

Get/Set the configuration file path.

Mode:

Get: The path of the config file as str. Default: "~/.config/pandas-ta/settings.json"
Set: The path to the config file.

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cores#

Manage the number of cpus to utilize for multiprocessing.

Mode:

Get: The number of cores for multiprocessing as Int.
Set: The number of cores Default: None

Disable multiprocessing

Set: df.ta.cores = 0

Multiprocessing caveats

Multiprocessing will not work when using the following keys: "col_names".
Multiprocessing may not work or complete as expected when indicator chaining.
- Chained indicators use non-default, ohlcv, sources as input Series.

exchange#

A label property of the major exchange the ohlcv data is associated with.

Mode:

Get: The exchange as a str.
Set: The exchange. Must be one of the following ta.EXCHANGE_TZ.keys(). Default: "NYSE"

time_range#

Useful for annualization.

Mode:

Get: Time elapsed between the first and last DateTemeIndex as float.
Set: Default: "years"

Methods#

See Also

TA DataFrame Constants

datetime_ordered

DataFrame DateTime ordered?

Returns:

Type	Description
`bool`	`True` if the DataFrame is DateTime ordered, otherwise `False`.

help

Help!

Parameters:

Name	Type	Description	Default
`s`	`str`	String to search for. Default: `""`	`''`

Returns:

Type	Description
`None \| TextIO`	Opens web browser to relevant Pandas TA website page or prints all search keywords.

indicators

List indicators.

Parameters:

Name	Type	Description	Default
`as_list`	`bool`	Return as a list. Default: `False`	`None`
`exclude`	`ListStr`	The passed in list will be excluded from the indicators list. Default: `None`	`None`

Returns:

Type	Description
`TextIO \| ListStr`	Prints list or returns a `ListStr`.

last_run

Detailed string of last run time.

Returns:

Type	Description
`str`	Detailed date and time of the lastest run.

reverse

Reverse the DataFrame inplace.

Returns:

Type	Description
`None`	DataFrame reversed inplace.

study

Applies the ta listed in a Study.

Other Parameters:

Name	Type	Description
`chunksize`	`int`	Multiprocessing Pool chunksize. Default: `df.ta.cores`
`cores`	`int`	Number of Multiprocessing cores. Default: `df.ta.cores`
`exclude`	`ListStr`	List of indicator names. Default: `[]`
`ordered`	`bool`	Run `ta` in order. Default: `True`
`returns`	`bool`	Return the DataFrame. Default: `False`
`timed`	`bool`	Print the process time. Default: `False`
`verbose`	`bool`	More verbose output. Default: `False`

Multiprocessing

Multiprocessing is not viable or efficient for some cases. Testing is required per case. See Multiprocessing for more information.

ticker

Download Historical ohlcv data as a Pandas DataFrame if yfinance package is installed. It also can run a ta.Study afterwards.

Parameters:

Name	Type	Description	Default
`ticker`	`str`	Any string for a ticker you would use with `yfinance`. Default: `"SPY"`	`None`
`period`	`str`	See the yfinance `history()` method for more options. Default: `"max"`	`None`
`interval`	`str`		`None`
`study`	`Study \| str`	After downloading, apply `Study` Default: `None`	`None`
`proxy`	`dict`	Proxy dictionary. Default: `{}`	`None`
`timed`	`bool`	Print download time to stdout. Default: `False`	`False`

Returns:

Type	Description
`DataFrame \| None`	ohlcv `df` or `None`

YFinance history parameters

yfinance
yfinance history()

Example

import panadas as pd
import pandas_ta as ta

# Simple
df = pd.DataFrame().ta.ticker("SPY", period="2y", timed=True)

# Built In Study
df = pd.DataFrame().ta.ticker("SPY", period="2y", study=ta.AllStudy, timed=True)

to_utc

Set the DataFrame index to UTC.

Returns:

Type	Description
`None`	Performs the operation.

Name	Type	Description	Default
`append`	`bool`	Concatenate if `True`. Drop if `False`. Default: `None`	required
`values`	`Array`	List/Numpy array of `values` to append/drop from the DataFrame.	required