Introduction to Pandas DataFrame

In this tutorial, you will learn

1. How to import the Pandas library?

2. How to create Series Object?

3. How to create a Pandas DataFrame?

4. How to display data in Pandas DataFrame?

5. How to get the Pandas DataFrame summary?

6. How to display the Pandas DataFrame Index?

7. How to transpose a DataFrame in Pandas?

8. How to check Null Values in Pandas DataFrame?

9. How to read files in a DataFrame in Pandas?

10. How to write Pandas DataFrame to a file?

1. Import the Libraries

import pandas as pd

2. Create a Series Object

series_object=pd.Series([1,2,3,4,5])
series_object

3. Create a Pandas DataFrame

df=pd.DataFrame({'Dates' :['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',
               '2020-01-05', '2020-01-06'] ,\
                'ID': [1,2,3,4,5,6],\
                'Names':['A','B','C','D','E','F'],\
                'Designation':['Manager','Employee','CEO','CTO','Manager','Employee']})
df

4. Display Data in Pandas DataFrame

df.head(1)

df.tail(1)

5. Pandas DataFrame Summary

df.describe()

6. Pandas DataFrame Index

df.index

7. Transpose Pandas DataFrame

df.T

8. Check Null Values in Pandas DataFrame

df.isna()

9. Read files in Pandas

csv_file=pd.read_csv("file_name.csv")
excel_file=pd.read_excel("file_name.xlsx")

10. Write Files in Pandas

pd.to_csv("file_name.extension")

Summary

1. Display DataFrame using .head( ) and .tail( ) method.

2. Transpose a DataFrame using .T( ) method.

3. Check null values using .isna( ) method.

4. Read files using pd.read_csv( ) method.

5. Write files using pd.to_csv( ) method.

PML