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Python | Pandas Series.to_frame()

  • Last Updated : 05 Feb, 2019
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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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