Python | Pandas Series.to_csv()

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index. Pandas Series.to_csv() function write the given series object to a comma-separated values (csv) file/format.

Syntax: Series.to_csv(*args, **kwargs) Parameter : path_or_buf : File path or object, if None is provided the result is returned as a string. sep : String of length 1. Field delimiter for the output file. na_rep : Missing data representation. float_format : Format string for floating point numbers. columns : Columns to write header : If a list of strings is given it is assumed to be aliases for the column names. index : Write row names (index). index_label : Column label for index column(s) if desired. If None is given, and header and index are True, then the index names are used. mode : Python write mode, default ‘w’. encoding : A string representing the encoding to use in the output file. compression : Compression mode among the following possible values: {‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}. quoting : Defaults to csv.QUOTE_MINIMAL. quotechar : String of length 1. Character used to quote fields. Returns : None or str

Example #1: Use Series.to_csv() function to convert the given series object to csv format. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio', 'Moscow'])

# Create the Datetime Index
didx = pd.DatetimeIndex(start ='2014-08-01 10:00', freq ='W', 
                     periods = 6, tz = 'Europe / Berlin') 

# set the index
sr.index = didx

# Print the series
print(sr)

Output : Now we will use Series.to_csv() function to convert the given Series object into a comma separated format. Python3 1==

# convert to comma-separated
sr.to_csv()

Output : As we can see in the output, the Series.to_csv() function has converted the given Series object into a comma-separated format.   Example #2: Use Series.to_csv() function to convert the given series object to csv format. Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([19.5, 16.8, None, 22.78, None, 20.124, None, 18.1002, None])

# Print the series
print(sr)

Output : Now we will use Series.to_csv() function to convert the given Series object into a comma separated format. Python3 1==

# convert to comma-separated
sr.to_csv()

Output : As we can see in the output, the Series.to_csv() function has converted the given Series object into a comma-separated format.