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')

Variable	Meaning
sep	separator character, can be an array
header	row number that contains column titles. remove if none
dtype	force any column to be interpreted as specific datatype
parse_dates	parse any column as datetime
encoding	file encoding e.g. utf-8 or ansi

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)

-  ⇤ ← Revision 3 as of 2020-04-08 16:01:34 → 
  Size: 1021
  Editor: Burathar
  Comment:
+   ← Revision 5 as of 2020-04-08 16:30:39 → ⇥
  Size: 1511
  Editor: Burathar
  Comment:
-Deletions are marked like this.
+Additions are marked like this.
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-== Standard import ==
+=== Standard import ===
-Line 18:
+Line 17:
-== Read CSV file ==
+=== Read CSV file ===
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+Line 23:
+|| '''Variable''' || '''Meaning'''                        ||
|| sep            || separator character, can be an array ||
|| header         || row number that contains column titles. remove if none ||
|| dtype          || force any column to be interpreted as specific [[https://pandas.pydata.org/pandas-docs/stable/getting_started/basics.html#basics-dtypes|datatype]] ||
|| parse_dates    || parse any column as datetime ||
|| encoding       || file encoding e.g. utf-8 or ansi ||
-Line 26:
+Line 30:
-== Renaming Columns ==
+=== Renaming Columns ===
-Line 30:
+Line 33:
-}}
+}}}
-Line 32:
+Line 35:
-== Do Y for each value in column X ==
+=== Do Y for each value in column X ===
-Line 36:
+Line 38:
-}}
+}}}
-Line 39:
+Line 41:
-== Renaming Columns ==
+=== Renaming Columns1 ===
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-}}
+}}}

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Description

Snippets

Standard import

Read CSV file

Renaming Columns

Do Y for each value in column X

Renaming Columns1