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_frame()
function is used to convert the given series object to a dataframe.
Syntax: Series.to_frame(name=None)
Parameter :
name : The passed name should substitute for the series name (if it has one).Returns : data_frame : DataFrame
Example #1: Use Series.to_frame()
function to convert the given series object to a dataframe.
# 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_frame()
function to convert the given series object to a dataframe.
# convert to dataframe sr.to_frame() |
Output :
As we can see in the output, the Series.to_frame()
function has successfully converted the given series object to a dataframe.
Example #2: Use Series.to_frame()
function to convert the given series object to a dataframe.
# 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_frame()
function to convert the given series object to a dataframe.
# convert to dataframe sr.to_frame() |
Output :
As we can see in the output, the Series.to_frame()
function has successfully converted the given series object to a dataframe.
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