import numpy as npimport pandas as pddf = pd.DataFrame({"sr": [1, 2, 3, 4], "name": ["Alex", np.nan, "Peter", "Klaus"], "age": [30, np.nan, 29, np.nan]})print(df.columns[df.isna().any()].tolist())

['name', 'age']

import numpy as npimport pandas as pddf = pd.DataFrame({"name": ["Alex", "John", "Peter", "Klaus"], "age": [30, np.nan, 29, np.nan]})print(df.isna())

    name    age
0  False  False
1  False   True
2  False  False
3  False   True

import pandas as pdd1 = pd.DataFrame({"Id": [1, 2], "name": ["Asha", "Ravi"]})d2 = pd.DataFrame({"Id": [2, 3], "city": ["Pune", "Delhi"]})print(d1.merge(d2, on="Id", how="outer"))

   Id  name   city
0   1  Asha    NaN
1   2  Ravi   Pune
2   3   NaN  Delhi

import pandas as pdd1 = pd.DataFrame({"Id": ["S1", "S2", "S3"], "Name": ["Ketan", "Yash", "Abhishek"], "marks1": [90, 87, 77]})d2 = pd.DataFrame({"Id": ["S2", "S3", "S4"], "marks2": [70, 65, 88]})print(d1.merge(d2, on="Id"))

   Id      Name  marks1  marks2
0  S2      Yash      87      70
1  S3  Abhishek      77      65

import pandas as pdd1 = pd.DataFrame({"Name": ["Yash", "Gaurav", "Sanket"], "Age": [30, 27, 28]})d2 = pd.DataFrame({"City": ["Pune", "Nagpur"]})print(pd.concat([d1, d2], axis=1))

     Name  Age    City
0    Yash   30    Pune
1  Gaurav   27  Nagpur
2  Sanket   28     NaN

import pandas as pdd1 = pd.DataFrame({"Id": [1, 2, 3], "Name": ["Yash", "Gaurav", "Sanket"], "Age": [30, 27, 28]})d2 = pd.DataFrame({"Id": [4, 5], "Name": ["Atharva", "Tanmay"], "Age": [26, 22]})print(pd.concat([d1, d2], ignore_index=True))

   Id     Name  Age
0   1     Yash   30
1   2   Gaurav   27
2   3   Sanket   28
3   4  Atharva   26
4   5   Tanmay   22

import pandas as pddf = pd.DataFrame({"Name": ["Ramesh", "Suresh", "Sanket"],                   "Address": ["297 shukrawar peth", "200 ravivar peth", "090 shanivar peth"]})df["words"] = df["Address"].str.replace(r"\d+", "", regex=True).str.strip()print(df)

     Name             Address           words
0  Ramesh  297 shukrawar peth  shukrawar peth
1  Suresh    200 ravivar peth    ravivar peth
2  Sanket   090 shanivar peth   shanivar peth

import pandas as pddf = pd.DataFrame({"Tweets": ["Pune #love", "#boycottmovie", "enjoying #peace #calm"]})df["tags"] = df["Tweets"].str.findall(r"#\w+")print(df)

                  Tweets             tags
0             Pune #love          [#love]
1          #boycottmovie  [#boycottmovie]
2  enjoying #peace #calm  [#peace, #calm]

import pandas as pddf = pd.DataFrame({"Company_mail": ["TCS tcs@yahoo.com", "Apple apple@icloud.com", "Google google@gmail.com"]})df["email"] = df["Company_mail"].str.extract(r"([\w.+-]+@[\w-]+\.[\w.]+)", expand=False)print(df)

              Company_mail             email
0        TCS tcs@yahoo.com     tcs@yahoo.com
1   Apple apple@icloud.com  apple@icloud.com
2  Google google@gmail.com  google@gmail.com

import pandas as pddf = pd.DataFrame({"Sales": [55000, 75000, 330000, 10000]})df["Sales_length"] = df["Sales"].astype(str).str.len()print(df)

    Sales  Sales_length
0   55000             5
1   75000             5
2  330000             6
3   10000             5