  Python | Pandas Index.value_counts ()

Counters | Python Methods and Functions

Index.value_counts() Pandas Index.value_counts() returns an object containing the number of unique values. The resulting object will be in descending order, so the first item is the most common item. Excludes NA values ​​by default.

Syntax: Index.value_counts (normalize = False, sort = True, ascending = False, bins = None, dropna = True)

Parameters:
normalize: If True then the object returned will contain the relative frequencies of the unique values.
sort: Sort by values ​​
ascending: Sort in ascending order
bins: Rather than count values, group them into half- open bins, a convenience for pd.cut, only works with numeric data
dropna: Don't include counts of NaN.

Returns: counts: Series

Example # 1: Use Index.value_counts () to count the number of unique values ​​in a given index.

 # import pandas as pd import pandas as pd   # Create index idx = pd.Index ([ 'Harry' , 'Mike' , ' Arther' , 'Nick' ,   ' Harry' , 'Arther' ], name = 'Student' )    # Print index print (idx)

Output: Let's find the count of all unique values ​​in the index.

 # find the number of unique values ​​in the index idx.value_counts ()

Output: The function returned a counter of all unique values ​​in the given index. Note that the object returned by the function contains occurrences of values ​​in descending order.

Example # 2: Use Index.value_counts () to find the count all unique values ​​in this index.

 # import pandas as pd import pandas as pd   # Create Index idx = pd .Index ([ 21 , 10 , 30 , 40 , 50 , 10 , 50 ])   # Print index print (idx)

Output: Let's count the occurrence of all unique values ​​in the index.

 # to count all # unique values in the index. idx.value_counts ()

Output: The function returned a counter of all unique values in the index.