Python | Pandas Series.get_dtype_counts()

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.get_dtype_counts() function return the counts of unique dtypes in this object.

Syntax: Series.get_values()

Parameter : None

Returns : dtype : Series

Example #1: Use Series.get_dtype_counts() function to return the count of unique dtype in the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', None, 'Rio'])

# Create the Index
index_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5']

# set the index
sr.index = index_

# Print the series
print(sr)

Output :

Now we will use Series.get_dtype_counts() function to return the count of unique dytpe in the given series object.

# return the count of dtypes
result = sr.get_dtype_counts()

# Print the result
print(result)

Output :

As we can see in the output, the Series.get_dtype_counts() function has returned the count of dtype in the given series object. It has returned object.

Example #2 : Use Series.get_dtype_counts() function to return the count of unique dtype in the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])

# Create the Index
index_ = pd.date_range('2010-10-09', periods = 11, freq ='M')

# set the index
sr.index = index_

# Print the series
print(sr)

Output :

Now we will use Series.get_dtype_counts() function to return the count of unique dytpe in the given series object.

# return the count of dtypes
result = sr.get_dtype_counts()

# Print the result
print(result)

Output :

As we can see in the output, the Series.get_dtype_counts() function has returned the count of dtype in the given series object. It has returned int64.