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Revision 1 as of 2020-04-08 15:48:30
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Editor: Burathar
Comment:
Revision 4 as of 2020-04-08 16:04:08
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Editor: Burathar
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Deletions are marked like this. Additions are marked like this.
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path = '/Path'
import pandas as pd
path = '/path/to/file(s)'
df = pd.read_csv(path + 'name.csv', sep=';', header=0, dtype={'Force String Column': str},
                 parse_dates=['Date Column'] encoding='utf-8')
Line 25: Line 26:
== Renaming Columns ==
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import numpy as np
import pandas as pd
dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)
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== Do Y for each value in column X ==

{{{#!highlight python
df.loc[:, ['X']] = df.loc[:, ['X']].apply(lambda x: x.Y)
}}}



== Renaming Columns1 ==

{{{#!highlight python
dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)
}}}

Description

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

Snippets

Standard import

   1 import numpy as np
   2 import pandas as pd

Read CSV file

   1 path = '/path/to/file(s)'
   2 df = pd.read_csv(path + 'name.csv', sep=';', header=0, dtype={'Force String Column': str}, 
   3                  parse_dates=['Date Column'] encoding='utf-8')

Renaming Columns

   1 dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)

Do Y for each value in column X

   1 df.loc[:, ['X']] = df.loc[:, ['X']].apply(lambda x: x.Y)

Renaming Columns1

   1 dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)

Howto/Python3/pandas (last edited 2020-04-08 17:13:18 by Burathar)