In Pandas, you can convert a Series to a dictionary using the to_dict()
method. This method creates a dictionary where the index labels of the Series become the keys, and the corresponding values become the values in the dictionary.
The to_dict()
method in Pandas allows you to convert a Series into a Python dictionary object. This method offers flexibility through its orient
parameter, which specifies the output format. The orient
parameter accepts values such as dict
, list
, series
, split
, records
, and index
. In this tutorial, I’ll explain how to convert a series into a Python dictionary object.
Key Points –
- Pandas provides the
to_dict()
method to convert a Series to a Python dictionary. - The resulting dictionary has the index labels of the Series as keys and the corresponding values as values.
- This conversion is useful for scenarios where dictionary-like operations or interfaces are required.
- The
orient
parameter into_dict()
allows customization of the output format, offering options likedict
,list
,series
,split
,records
, andindex
.
Quick Examples of Convert Series to Dict
Below are quick examples of converting the pandas series to Dictionary.
# Quick examples of convert series to dict
# Example 1 : Create Pandas series
courses = pd.Series(['Java', 'Spark', 'PySpark','Pandas','NumPy', 'Python'])
# Example 2 : Customize the index series
courses = pd.Series(['Java', 'Spark', 'PySpark','Pandas','NumPy', 'Python'],
index = ['Course1', 'Course2', 'Course3', 'Course4', 'Course5','Course6'])
# Example 3 : Convert Series to dictionary
dict = courses.to_dict()
Syntax of Pandas Series.to_dict()
Following is the syntax of the Series.to_dict()
.
# Syntax of series.to_dict()
series.to_dict(orient='dict', into=)
Initialize Pandas Series
A Pandas Series is a core data structure in the Pandas library, representing one-dimensional data with labeled indices. It can hold various data types, such as strings, integers, floats, and other Python objects.
First, let’s create a series and change it to a Python dictionary. Note that our series contains indices and values.
import pandas as pd
# Customize the index series
courses = pd.Series(['Java', 'Spark', 'PySpark','Pandas','NumPy', 'Python'],
index = ['Course1', 'Course2', 'Course3', 'Course4', 'Course5','Course6'])
print("Create Pandas Series:\n", courses)
Yields below output.
Convert Pandas Series to Dictionary
You can use the pandas Series.to_dict()
function to convert a Series to a dictionary (dict). If you want to convert DataFrame to Dictionary you can use DataFrame.to.dict()
function.
Let’s pass the Series object which we want to convert to a dictionary into this function, it will return the dictionary, where the keys are indices and values are values of the given series.
# Convert Series to dictionary
dict = courses.to_dict()
print("After converting a Series to dictionary:\n", dict)
print("Type of the object:\n", type(dict))
Yields below output.
FAQ on Convert Series to Dictionary(Dict) in Pandas
You can convert a Pandas Series to a dictionary using the .to_dict()
method. The index values of the Series will become the keys of the dictionary, and the corresponding values in the Series will become the dictionary values.
The .to_dict()
method will exclude any missing data (NaN
) in the Series when converting to a dictionary. If you want to handle missing values, you should first fill or drop the missing values before conversion.
You can convert a Series with a MultiIndex to a dictionary. The MultiIndex will be flattened, and the resulting dictionary will use the tuple of index values as keys.
If the Series has duplicate index values, converting it to a dictionary will overwrite the earlier entries with the same key. Only the last occurrence of a key will be kept in the dictionary.
You can manipulate the values before converting to a dictionary, such as applying a function to each value using .apply()
.
Conclusion
In this article, you have learned pandas.Series.to_dict()
method and using this method you can convert Pandas Series to Python dictionary objects by converting indices as keys and the corresponding values of indices as values.
Happy Learning !!
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