Create Pandas DataFrames from Unique Values in one Column

Question

I have a Pandas dataframe with 1000s of rows. and it has the Names column includes the customer names and their records. I want to create individual dataframes

Answer 1

maybe i get you wrong but

when

for x in customerNames:
    x = DataFrame.loc[DataFrame['customer name'] == x]
x

gives you the right output for the last list entry its because your output is out of the indent of the loop

import pandas as pd

customer_df = pd.DataFrame.from_items([('A', ['Jean', 'France']), ('B', ['James', 'USA'])],
                        orient='index', columns=['customer', 'country'])

customer_list = ['James', 'Jean']

for x in customer_list:
    x = customer_df.loc[customer_df['customer'] == x]
    print(x)
    print('now I could append the data to something new')

you get the output:

  customer country
B    James     USA
now I could append the data to something new
  customer country
A     Jean  France
now I could append the data to something new

Or if you dont like loops you could go with

import pandas as pd

customer_df = pd.DataFrame.from_items([('A', ['Jean', 'France']), ('B', ['James', 'USA']),('C', ['Hans', 'Germany'])],
                        orient='index', columns=['customer', 'country'])

customer_list = ['James', 'Jean']


print(customer_df[customer_df['customer'].isin(customer_list)])

Output:

  customer country
A     Jean  France
B    James     USA

df.isin is better explained under:How to implement 'in' and 'not in' for Pandas dataframe