mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-29 13:32:08 +00:00
59d8b36bb0
* Fixes * Update stocks_helper.py * update git-actions set-output to new format * Update stocks_helper.py * Update terminal_helper.py * removed LineAnnotateDrawer from qa_view * lint * few changes * updates * sdk auto gen modules done * Update stocks_helper.py * updates to changed imports, and remove first sdk_modules * Update generate_sdk.py * Update generate_sdk.py * pylint * revert stocks_helper * Update generate_sdk.py * Update sdk.py * Update generate_sdk.py * full auto generation, added sdk.py/controllers creation * missed enable forecasting * added running black in subprocess after sdk files generation completes * removed deleted sdk_arg_logger * comment out tests * property doc fix * clean up * Update generate_sdk.py * make trailmap classes useable for doc generation * Update generate_sdk.py * added lineon to trailmap class for linking to func in markdown * changed lineon to dict * added full_path to trailmap for linking in docs * updated portfolio * feat: initial files * feat: added meta head * feat: added funcdef * added func_def to trailmap attributes for markdown in docs, added missing type hints to covid functions * feat: added view and merged with jaun * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * Update generate_sdk.py * init * fix returns * fix: random stuff * fix: random * fixed encoding issue on windows * fix: generate tabs * update * Update generate_sdk_markdown.py * Create .pydocstyle.ini * added type hint classes for views * fixes * alt, ba * alt-economy * Update finviz_compare_model.py * fixs * Update substack_model.py * Update generate_sdk.py * last of my section * porfolio * po * Update optimizer_model.py * fixing more things * few more * keys done * update * fixes * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * mypy forecast fix * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * Update generate_sdk_markdown.py * fixes * forecast fixes * one more fix * Update coinbase_model.py * Update generate_sdk_markdown.py Co-authored-by: Colin Delahunty <72827203+colin99d@users.noreply.github.com> Co-authored-by: James Maslek <jmaslek11@gmail.com> Co-authored-by: jose-donato <zmcdonato@gmail.com> Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
"""Denomination Helper functions"""
|
|
|
|
from typing import Literal, Tuple, Callable, Dict
|
|
import pandas as pd
|
|
from pandas._typing import Axis
|
|
|
|
DENOMINATION = Literal[
|
|
"Trillions", "Billions", "Millions", "Tens of thousands", "Thousands", "Units", ""
|
|
]
|
|
|
|
|
|
def transform(
|
|
df: pd.DataFrame,
|
|
sourceDenomination: DENOMINATION = "Units",
|
|
targetDenomination: DENOMINATION = None,
|
|
maxValue: float = None,
|
|
axis: Axis = 0,
|
|
skipPredicate: Callable[[pd.Series], bool] = None,
|
|
) -> Tuple[pd.DataFrame, DENOMINATION]:
|
|
"""Transforms data frame by denomination.
|
|
|
|
Args:
|
|
df (pd.DataFrame): Source data frame
|
|
sourceDenomination (DENOMINATION, optional): Current denomination. Defaults to Units.
|
|
targetDenomination (DENOMINATION, optional): Desired denomination. Defaults to None, meaning we will find it.
|
|
maxValue (float, optional): Max value of the data frame. Defaults to None, meaning df.max().max() will be used.
|
|
axis (Axis, optional): Axis to apply to skip predicate. Defaults to 0.
|
|
skipPredicate (Callable[[pd.Series], bool], optional): Predicate for skipping a transform.
|
|
Returns:
|
|
pd.DataFrame
|
|
Tuple[pd.DataFrame, DENOMINATION]: Pair of transformed data frame and applied denomination.
|
|
"""
|
|
|
|
def apply(
|
|
df: pd.DataFrame, source: DENOMINATION, target: DENOMINATION
|
|
) -> pd.DataFrame:
|
|
multiplier = get_denominations()[source] / get_denominations()[target]
|
|
df = df.astype(float)
|
|
return df.apply(
|
|
lambda series: series
|
|
if skipPredicate is not None and skipPredicate(series)
|
|
else series * multiplier,
|
|
axis,
|
|
)
|
|
|
|
if targetDenomination is not None:
|
|
return (
|
|
apply(df, sourceDenomination, targetDenomination),
|
|
targetDenomination,
|
|
)
|
|
|
|
if maxValue is None:
|
|
maxValue = df.max(numeric_only=True).max(numeric_only=True)
|
|
|
|
foundTargetDenomination = get_denomination(maxValue)
|
|
|
|
return (
|
|
apply(df, sourceDenomination, foundTargetDenomination[0]),
|
|
foundTargetDenomination[0],
|
|
)
|
|
|
|
|
|
def get_denominations() -> Dict[DENOMINATION, float]:
|
|
"""Gets all supported denominations and their lower bound value
|
|
|
|
Returns:
|
|
Dict[DENOMINATION, int]: All supported denominations and their lower bound value
|
|
"""
|
|
return {
|
|
"Trillions": 1_000_000_000_000,
|
|
"Billions": 1_000_000_000,
|
|
"Millions": 1_000_000,
|
|
"Tens of thousands": 10_000,
|
|
"Thousands": 1_000,
|
|
"Units": 1,
|
|
}
|
|
|
|
|
|
def get_denomination(value: float) -> Tuple[DENOMINATION, float]:
|
|
"""Gets denomination that fits the supplied value.
|
|
If no denomination found, 'Units' is returned.
|
|
|
|
Args:
|
|
value (int): Value
|
|
|
|
Returns:
|
|
Tuple[DENOMINATION, int]:Denomination that fits the supplied value
|
|
"""
|
|
return next((x for x in get_denominations().items() if value >= x[1]), ("Units", 1))
|