Pythonic type hints with pandas?

Why not just use pd.DataFrame?

import pandas as pd
def csv_to_df(path: str) -> pd.DataFrame:
    return pd.read_csv(path, skiprows=1, sep='\t', comment='#')

Result is the same:

> help(csv_to_df)
Help on function csv_to_df in module __main__:
csv_to_df(path:str) -> pandas.core.frame.DataFrame

Check out the answer given here which explains the usage of the package data-science-types.

pip install data-science-types

Demo

# program.py

import pandas as pd

df: pd.DataFrame = pd.DataFrame({'col1': [1,2,3], 'col2': [4,5,6]}) # OK
df1: pd.DataFrame = pd.Series([1,2,3]) # error: Incompatible types in assignment

Run using mypy the same way:

$ mypy program.py

Now there is a pip package that can help with this. https://github.com/CedricFR/dataenforce

You can install it with pip install dataenforce and use very pythonic type hints like:

def preprocess(dataset: Dataset["id", "name", "location"]) -> Dataset["location", "count"]:
    pass

I'm currently doing the following:

from typing import TypeVar
PandasDataFrame = TypeVar('pandas.core.frame.DataFrame')
def csv_to_df(path: str) -> PandasDataFrame:
    return pd.read_csv(path, skiprows=1, sep='\t', comment='#')

Which gives:

> help(csv_to_df)
Help on function csv_to_df in module __main__:

csv_to_df(path:str) -> ~pandas.core.frame.DataFrame

Don't know how pythonic that is, but it's understandable enough as a type hint, I find.