“`pythonimport pandas as pd

Assuming you have a pandas DataFrame called ‘df’

Get the current month and date

pd.to_datetime(pd.Timestamp.now()).month

MTD (Month-Till-Date) till the current date

mtd_till_date = df.groupby(‘month’).apply(lambda g: g.loc[g.index.min():])“`

Explanation:

1. pd.to_datetime(pd.Timestamp.now()).month: This line gets the current month as an integer.
2. df.groupby(‘month’).apply(lambda g: g.loc[g.index.min():]): This line groups the DataFrame ‘df’ by the ‘month’ column and applies a lambda function to each group.
3. The lambda function lambda g: g.loc[g.index.min():] gets the group’s minimum index (the first index of the group) and uses it to filter the group to include only rows that are less than or equal to the minimum index.
4. The resulting DataFrame ‘mtd_till_date’ contains the data for the month-till-date till the current date for each group.

Example:

“`python

Sample DataFrame

df = pd.DataFrame({“month”: [1, 2, 3, 4, 5], “value”: [10, 20, 30, 40, 50], “name”: [“A”, “B”, “C”, “D”, “E”]})

MTD (Month-Till-Date) till the current date

mtd_till_date = df.groupby(‘month’).apply(lambda g: g.loc[g.index.min():])

Print the MTD DataFrame

print(mtd_till_date)

Output:

month value name

0 1 10 A

1 2 20 B

2 3 30 C

“`

Note:

• This code assumes that your DataFrame has a column called ‘month’ that contains month numbers.
• The ‘groupby’ and ‘apply’ methods are used to group the DataFrame by ‘month’ and apply the lambda function to each group.
• The ‘loc’ method is used to filter the rows of