Save pandas dataframe to a csv file

Parameters#

Parameter	Description
path_or_buf	string or file handle, default None File path or object, if None is provided the result is returned as a string.
sep	character, default ‘,’ Field delimiter for the output file.
na_rep	string, default ‘’ Missing data representation
float_format	string, default None Format string for floating point numbers
columns	sequence, optional Columns to write
header	boolean or list of string, default True Write out column names. If a list of string is given it is assumed to be aliases for the column names
index	boolean, default True Write row names (index)
index_label	string or sequence, or False, default None Column label for index column(s) if desired. If None is given, and header and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex. If False do not print fields for index names. Use index_label=False for easier importing in R
nanRep	None deprecated, use na_rep
mode	str Python write mode, default ‘w’
encoding	string, optional A string representing the encoding to use in the output file, defaults to ‘ascii’ on Python 2 and ‘utf-8’ on Python 3.
compression	string, optional a string representing the compression to use in the output file, allowed values are ‘gzip’, ‘bz2’, ‘xz’, only used when the first argument is a filename
line_terminator	string, default ‘n’ The newline character or character sequence to use in the output file
quoting	optional constant from csv module defaults to csv.QUOTE_MINIMAL
quotechar	string (length 1), default ‘”’ character used to quote fields
doublequote	boolean, default True Control quoting of quotechar inside a field
escapechar	string (length 1), default None character used to escape sep and quotechar when appropriate
chunksize	int or None rows to write at a time
tupleize_cols	boolean, default False write multi_index columns as a list of tuples (if True) or new (expanded format) if False)
date_format	string, default None Format string for datetime objects
decimal	string, default ‘.’ Character recognized as decimal separator. E.g. use ‘,’ for European data
## Create random DataFrame and write to .csv
Create a simple DataFrame.

import numpy as np
import pandas as pd

# Set the seed so that the numbers can be reproduced.
np.random.seed(0)  

df = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))

# Another way to set column names is "columns=['column_1_name','column_2_name','column_3_name']"

df

      A         B         C
0  1.764052  0.400157  0.978738
1  2.240893  1.867558 -0.977278
2  0.950088 -0.151357 -0.103219
3  0.410599  0.144044  1.454274
4  0.761038  0.121675  0.443863

Now, write to a CSV file:

df.to_csv('example.csv', index=False)

Contents of example.csv:

A,B,C
1.76405234597,0.400157208367,0.978737984106
2.2408931992,1.86755799015,-0.977277879876
0.950088417526,-0.151357208298,-0.103218851794
0.410598501938,0.144043571161,1.45427350696
0.761037725147,0.121675016493,0.443863232745

Note that we specify index=False so that the auto-generated indices (row #s 0,1,2,3,4) are not included in the CSV file. Include it if you need the index column, like so:

df.to_csv('example.csv', index=True)  # Or just leave off the index param; default is True

Contents of example.csv:

,A,B,C
0,1.76405234597,0.400157208367,0.978737984106
1,2.2408931992,1.86755799015,-0.977277879876
2,0.950088417526,-0.151357208298,-0.103218851794
3,0.410598501938,0.144043571161,1.45427350696
4,0.761037725147,0.121675016493,0.443863232745

Also note that you can remove the header if it’s not needed with header=False. This is the simplest output:

df.to_csv('example.csv', index=False, header=False)

Contents of example.csv:

1.76405234597,0.400157208367,0.978737984106
2.2408931992,1.86755799015,-0.977277879876
0.950088417526,-0.151357208298,-0.103218851794
0.410598501938,0.144043571161,1.45427350696
0.761037725147,0.121675016493,0.443863232745

The delimiter can be set by sep= argument, although the standard separator for csv files is ',' .

df.to_csv('example.csv', index=False, header=False, sep='\t')

1.76405234597    0.400157208367    0.978737984106
2.2408931992    1.86755799015    -0.977277879876
0.950088417526    -0.151357208298    -0.103218851794
0.410598501938    0.144043571161    1.45427350696
0.761037725147    0.121675016493    0.443863232745

Save Pandas DataFrame from list to dicts to csv with no index and with data encoding

import pandas as pd
data = [
    {'name': 'Daniel', 'country': 'Uganda'},
    {'name': 'Yao', 'country': 'China'},
    {'name': 'James', 'country': 'Colombia'},
]
df = pd.DataFrame(data)
filename = 'people.csv'
df.to_csv(filename, index=False, encoding='utf-8')