Pandas create column if date in between two dates

First change eventDate to datetime format, then add a simple condition.

df.eventDate = pd.to_datetime(df.eventDate)
df['validDate'] = df.eventData.apply(lambda x: "Yes" if pd.to_datetime(startDate) <= x <= pd.to_datetime(endDate) else "No")

Note pandas to_datetime will automatically parse the date in the required format.

startDate_dt = datetime.datetime.strptime(startDate, "%Y-%m-%d")
endDate_dt = datetime.datetime.strptime(endDate, "%Y-%m-%d")

df["validDate"] = df["eventDate"].apply(lambda x: \
        (datetime.datetime.strptime(x, "%Y-%m-%d") <= endDate_dt) & \
         (datetime.datetime.strptime(x, "%Y-%m-%d") >= startDate_dt))

Let's say the eventDate column contains all days for September:

import pandas as pd

df = pd.DataFrame({
    "eventDate": pd.date_range(start="2022-09-01", end="2022-09-30").strftime('%Y-%m-%d'),
})

And you want the dates to be "valid" only for the first week of September. You could do it this way:

from datetime import datetime

d1 = datetime(year=2022, month=9, day=1) # first day valid
d2 = datetime(year=2022, month=9, day=7) # last day valid

def is_date_valid(str_date: str):
    dt = datetime.fromisoformat(str_date)
    return ((dt >= d1) and (dt <= d2))

df["validDate"] = df["eventDate"].apply(is_date_valid)

The result you get:

df.head(10)

    eventDate   validDate
0   2022-09-01  True
1   2022-09-02  True
2   2022-09-03  True
3   2022-09-04  True
4   2022-09-05  True
5   2022-09-06  True
6   2022-09-07  True
7   2022-09-08  False
8   2022-09-09  False
9   2022-09-10  False