In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/src/sample_pandas_normal.csv', index_col=0)

print(df)


    

    




         age state  point
name                     
Alice     24    NY     64
Bob       42    CA     92
Charlie   18    CA     70
Dave      68    TX     70
Ellen     24    CA     88
Frank     30    NY     57

In [3]:

    

df.to_csv('data/dst/to_csv_out.csv')


    

In [4]:

    

df.to_csv('data/dst/to_csv_out_columns.csv', columns=['age'])


    

In [5]:

    

df.to_csv('data/dst/to_csv_out_header_index.csv', header=False, index=False)


    

In [6]:

    

df.to_csv('data/dst/to_csv_out.tsv', sep='\t')


    

In [7]:

    

df.to_csv('data/dst/to_csv_out_a.csv')
df.to_csv('data/dst/to_csv_out_a.csv', mode='a', header=False)


    

In [8]:

    

df.to_csv('data/dst/to_csv_out_a_new_column.csv')


    

In [9]:

    

df = pd.read_csv('data/dst/to_csv_out_a_new_column.csv', index_col=0)

print(df)


    

    




         age state  point
name                     
Alice     24    NY     64
Bob       42    CA     92
Charlie   18    CA     70
Dave      68    TX     70
Ellen     24    CA     88
Frank     30    NY     57

In [10]:

    

df['new_col'] = 'new data'

print(df)


    

    




         age state  point   new_col
name                               
Alice     24    NY     64  new data
Bob       42    CA     92  new data
Charlie   18    CA     70  new data
Dave      68    TX     70  new data
Ellen     24    CA     88  new data
Frank     30    NY     57  new data

In [11]:

    

df.to_csv('data/dst/to_csv_out_a_new_column.csv')