Pandas DataFrame.to_sparse() Method
Last Updated :
31 Mar, 2023
Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas.
Pandas DataFrame.to_sparse
Pandas DataFrame.to_sparse() function convert to SparseDataFrame. The function implements the sparse version of the DataFrame meaning that any data matching a specific value it’s omitted in the representation. The sparse DataFrame allows for more efficient storage.
Syntax: DataFrame.to_sparse(fill_value=None, kind=’block’)
Parameter :
- fill_value : The specific value that should be omitted in the representation.
- kind : {‘block’, ‘integer’}, default ‘block’
Returns : SparseDataFrame
Pandas SparseDataFrame Example
Example 1: Use DataFrame.to_sparse() function to convert the given Dataframe to a SparseDataFrame for efficient storage.
Python3
import pandas as pd
df = pd.DataFrame({ 'Weight' : [ 45 , 88 , 56 , 15 , 71 ],
'Name' : [ 'Sam' , 'Andrea' , 'Alex' , 'Robin' , 'Kia' ],
'Age' : [ 14 , 25 , 55 , 8 , 21 ]})
index_ = pd.date_range( '2010-10-09 08:45' , periods = 5 , freq = 'H' )
df.index = index_
print (df)
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Output :
Now we will use DataFrame.to_sparse() function to convert the given dataframe to a SparseDataFrame.
Python3
result = df.to_sparse()
print (result)
print ( type (result))
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Output :
As we can see in the output, the DataFrame.to_sparse() function has successfully converted the given dataframe to a SparseDataFrame type.
Example 2: Use DataFrame.to_sparse() function to convert the given Dataframe to a SparseDataFrame for efficient storage.
Python3
import pandas as pd
df = pd.DataFrame({ "A" : [ 12 , 4 , 5 , None , 1 ],
"B" : [ 7 , 2 , 54 , 3 , None ],
"C" : [ 20 , 16 , 11 , 3 , 8 ],
"D" : [ 14 , 3 , None , 2 , 6 ]})
index_ = [ 'Row_1' , 'Row_2' , 'Row_3' , 'Row_4' , 'Row_5' ]
df.index = index_
print (df)
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Output :
Now we will use DataFrame.to_sparse() function to convert the given dataframe to a SparseDataFrame.
Python3
result = df.to_sparse()
print (result)
print ( type (result))
|
Output :
As we can see in the output, the DataFrame.to_sparse() function has successfully converted the given Dataframe to a SparseDataFrame type.
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