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 2 as of 2020-04-08 15:53:19 → 
  Size: 641
  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.
 Line 11:
-== Standard import ==
+=== Standard import ===
-Line 18:
+Line 17:
-== Read CSV file ==
+=== Read CSV file ===
-Line 22:
+Line 20:
-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')
}}}
|| '''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 ||

=== Renaming Columns ===
{{{#!highlight python
dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)
-Line 25:
+Line 35:
+=== Do Y for each value in column X ===
-Line 26:
+Line 37:
-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')
+df.loc[:, ['X']] = df.loc[:, ['X']].apply(lambda x: x.Y)
-Line 29:
+Line 39:
+=== Renaming Columns1 ===
{{{#!highlight python
dt.rename(columns={'File column name 1': 'Column1', 'File column name 2': '2'}, inplace=True)
}}}

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Description

Snippets

Standard import

Read CSV file

Renaming Columns

Do Y for each value in column X

Renaming Columns1