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Python | Pandas Series.to_dict()

Last Updated : 11 Jul, 2024
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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_dict()

function is used to convert the given Series object to {label -> value} dict or dict-like object.

Syntax: Series.to_dict(into=) Parameter : into : The collections.Mapping subclass to use as the return object. Returns : value_dict : collections.Mapping

Example #1:

Use

Series.to_dict()

function to convert the given series object to a dictionary.

Python
# 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_dict()

function to convert the given series object to a dictionary.

Python3 1==
# convert to dictionary
sr.to_dict()

Output :

As we can see in the output, the

Series.to_dict()

function has successfully converted the given series object to a dictionary.  

Example #2:

Use

Series.to_dict()

function to convert the given series object to a dictionary.

Python
# 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_dict()

function to convert the given series object to a dictionary.

Python3 1==
# convert to dictionary
sr.to_dict()

Output :

As we can see in the output, the

Series.to_dict()

function has successfully converted the given series object to a dictionary.


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