How to write simple function which will return rows based on column with date in Python Pandas?-CodePudding

I have DataFrame in Python Pandas like below:

ID	DATE	LOG
123	2021-12-31	2021-12-30
445	2021-12-31	2022-01-15
2232	2021-12-31	NaN

And I need to create function which argument will be date from column "DATE" and this function will return ID of clients from column "ID" who were logged (column "LOG") before date from column "DATE" or have NaN in column "LOG". So fo example:

my_function(df["DATE"])

will return because these clients who have LOG < DATE or LOG == NaN

ID
-----
123
2232

CodePudding user response：

You could write your condition and use boolean indexing:

def my_function(df):
    msk = (df['DATE'] > df['LOG']) | df['LOG'].isna()
    return df.loc[msk, 'ID']

>>> my_function(df)
0     123
2    2232
Name: ID, dtype: int64

CodePudding user response：

This function takes two arguments to print your clients ID where LOG is not NaN and have logged before date time value from "DATE"

import numpy as np

def my_function(df, date):
    return df["ID"].loc((not np.isnan(df["LOG"])) | (df["DATE"]>df["LOG"]))