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_json() function is used to convert the object to a JSON string. Also note that NaN’s and None will be converted to null and datetime objects will be converted to UNIX timestamps.
Syntax: Series.to_json(path_or_buf=None, orient=None, date_format=None, double_precision=10, force_ascii=True, date_unit=’ms’, default_handler=None, lines=False, compression=’infer’, index=True)
Parameter :
path_or_buf : File path or object. If not specified, the result is returned as a string.
orient : Indication of expected JSON string format.
date_format : None, ‘epoch’, ‘iso’}
double_precision : The number of decimal places to use when encoding floating point values.
force_ascii : Force encoded string to be ASCII.
date_unit : string, default ‘ms’ (milliseconds)
default_handler : callable, default None
lines : bool, default False
compression : {‘infer’, ‘gzip’, ‘bz2’, ‘zip’, ‘xz’, None}Returns : Json string
Example #1: Use Series.to_json() function to convert the given series object to JSON string.
# 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_json() function to convert the given series object to JSON string.
# convert to JSON string sr.to_json() |
Output :
As we can see in the output, the Series.to_json() function has successfully converted the given series object to JSON string.
Example #2: Use Series.to_json() function to convert the given series object to JSON string.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([19.5, 16.8, 22.78, 20.124, 18.1002]) # Print the series print(sr) |
Output :
Now we will use Series.to_json() function to convert the given series object to JSON string.
# convert to JSON string sr.to_json() |
Output :
As we can see in the output, the Series.to_json() function has successfully converted the given series object to JSON string.
