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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') |
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== 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) }}} |
Contents
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
Read CSV file
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)