pandas Pandas IO tools (reading and saving data sets) Reading csv file into DataFrame
Example
Example for reading file data_file.csv such as:
File:
index,header1,header2,header3
1,str_data,12,1.4
3,str_data,22,42.33
4,str_data,2,3.44
2,str_data,43,43.34
7, str_data, 25, 23.32
Code:
pd.read_csv('data_file.csv')
Output:
index header1 header2 header3
0 1 str_data 12 1.40
1 3 str_data 22 42.33
2 4 str_data 2 3.44
3 2 str_data 43 43.34
4 7 str_data 25 23.32
Some useful arguments:
-
sepThe default field delimiter is a comma,. Use this option if you need a different delimiter, for instancepd.read_csv('data_file.csv', sep=';') -
index_colWithindex_col = n(nan integer) you tell pandas to use columnnto index the DataFrame. In the above example:pd.read_csv('data_file.csv', index_col=0)Output:
header1 header2 header3 index 1 str_data 12 1.40 3 str_data 22 42.33 4 str_data 2 3.44 2 str_data 43 43.34 7 str_data 25 23.32
-
skip_blank_linesBy default blank lines are skipped. Useskip_blank_lines=Falseto include blank lines (they will be filled withNaNvalues)pd.read_csv('data_file.csv', index_col=0,skip_blank_lines=False)Output:
header1 header2 header3 index 1 str_data 12 1.40 3 str_data 22 42.33 4 str_data 2 3.44 2 str_data 43 43.34 NaN NaN NaN NaN 7 str_data 25 23.32 -
parse_datesUse this option to parse date data.File:
date_begin;date_end;header3;header4;header5 1/1/2017;1/10/2017;str_data;1001;123,45 2/1/2017;2/10/2017;str_data;1001;67,89 3/1/2017;3/10/2017;str_data;1001;0Code to parse columns
0and1as dates:pd.read_csv('f.csv', sep=';', parse_dates=[0,1])Output:
date_begin date_end header3 header4 header5 0 2017-01-01 2017-01-10 str_data 1001 123,45 1 2017-02-01 2017-02-10 str_data 1001 67,89 2 2017-03-01 2017-03-10 str_data 1001 0By default, the date format is inferred. If you want to specify a date format you can use for instance
dateparse = lambda x: pd.datetime.strptime(x, '%d/%m/%Y') pd.read_csv('f.csv', sep=';',parse_dates=[0,1],date_parser=dateparse)Output:
date_begin date_end header3 header4 header5 0 2017-01-01 2017-10-01 str_data 1001 123,45 1 2017-01-02 2017-10-02 str_data 1001 67,89 2 2017-01-03 2017-10-03 str_data 1001 0
More information on the function's parameters can be found in the official documentation.
