CODEWITHSUNDEEP
pythonlistpandasdataframeconditional-statements
Gonzalo
Gonzalo

Reputation: 1114

Use of Pandas to slice and create Lists

After some research on csv / pandas / etc to manipulate a huge csv file I decide to use pandas to slice just the information I need. Now I am able to get just what I need using a filter i.e. "Name"="Greg" where I just see rows when the column Name has Greg. However I would like now to create a pyhton List with all information of a specific column (i.e. City). How could I do that? Then I will work just with the List to sort, count, etc.

What I have:

import pandas as pd

all_data = pd.read_csv(
    'myfile.csv',           # file name
    sep=',',                    # column separator
    quotechar='"',              # quoting character
    encoding='utf-16',
    na_values=0,                # fill missing values with 0
    usecols=[0,1,3],          # columns to use
    decimal='.')                # symbol for decimals



slice1 = all_data[all_data['Name'] == 'Greg']
print (slice1)

Example of print (slice1):

enter image description here

Upvotes: 1

Views: 3770

Answers (1)

jezrael
jezrael

Reputation: 863281

You can use ix with tolist:

#output is Series - column City
slice1 = all_data.ix[all_data['Name'] == 'Greg', 'City']

#generate list from Series
L = all_data.ix[all_data['Name'] == 'Greg', 'City'].tolist()

Sample:

import pandas as pd

all_data = pd.DataFrame({'Name':['Greg','Greg','Greg','Adam'],
                         'Coutry':['US','UK','UK','UK'],
                         'City':['LA','LD','RE','LB']},
                         index=[221,564,800,500])

print (all_data)
    City Coutry  Name
221   LA     US  Greg
564   LD     UK  Greg
800   RE     UK  Greg
500   LB     UK  Adam

slice1 = all_data.ix[all_data['Name'] == 'Greg', 'City']
print (slice1)
221    LA
564    LD
800    RE
Name: City, dtype: object

L = all_data.ix[all_data['Name'] == 'Greg', 'City'].tolist()
print (L)
['LA', 'LD', 'RE']

Upvotes: 1

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