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⇤ ← Revision 2 as of 2020-04-08 15:53:19 →
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Editor: Burathar
Comment:
← Revision 3 as of 2020-04-08 16:01:34 → ⇥
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Editor: Burathar
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Deletions are marked like this. Additions are marked like this.
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import pandas as pd df = pd.read_csv(path + 'name.csv', sep=';', header=0, dtype={'Force String Column': str},
                 parse_dates=['Date Column'] encoding='utf-8')
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== Renaming Columns ==
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import numpy as np
df = pd.read_csv(path + 'name.csv', sep=';', header=0, dtype={'Force String Column': str}, parse_dates=['Date Column'] encoding='utf-8')
}}}		 dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)
}}

== Do Y for each value in column X ==

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



== Renaming Columns ==

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

Contents

  1. Description
  2. Snippets
    1. Standard import
    2. Read CSV file
    3. Renaming Columns

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

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