value_counts() in pandas | value_counts in pandas example on entire dataframe & column

In this pandas tutorial, we will discuss about:

• value_counts pandas method use in pandas DataFrame,
• value_counts on column pandas,
• value_counts in pandas dataframe(when applied on entire dataframe),
• value_counts in pandas example,

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First lets create a dataframe that will be used to demonstrate this method - value_counts pandas dataframe.

 

DataFrame in pandas is two dimensional data structure that will store data in two dimensional format. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns.

 

We create DataFrame using DataFrame() method. But this is available in pandas module, so we have to import pandas module.

Syntax:

pandas.DataFrame(data)

Where, data is the input dataframe , The data can be a dictionary that stores list of values with specified key

 

Example: Create pandas dataframe

In this example, we will create dataframe with 4 rows and 4 columns with college data and assign indices through index parameter.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":['1200','3422','5644','670']

                   },index=['one','two','three','four'])

#display the dataframe
print(data)

Output: dataframe is created below

      college_id       college_name college_address Total Staff
one        c-001  vignan university          guntur        1200
two        c-021               vvit          guntur        3422
three      c-002           RVR - JC          guntur        5644
four       c-004  Andhra University          guntur         670

Now lets apply this value_counts on column pandas and entire dataframe using value_counts() in pandas.

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What is value_counts in pandas?

value_counts() in pandas is used to return the count of occurance of each value in a dataframe or in a particular column.

If no column is mentioned, value_counts() in pandas will return the count of each row.

Syntax:

dataframe.value_counts(sort,ascending,dropna)

where, dataframe is the input dataframe.

Parameters:

1. sort - this is used to sort the data that is returned from the dataframe
2. ascending is used to get the data in ascending or descending order.It will take boolean values. If it is True → then the data is sorted in ascending order and if its set to false → the data is sorted in descending order.
3. dropna is used to drop / remove if any null values are present in the dataframe.

Now lets see few value_counts in pandas example.

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Example 1: value_counts in pandas example applied on entire dataframe

In this value_counts in pandas example, we are applying value_counts() on entire dataframe.

import pandas as pd

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":['1200','3422','5644','670']

                   },index=['one','two','three','four'])

#display the dataframe by applying value_counts
print(data.value_counts())

Output: value count pandas dataframe result for above code

college_id  college_name       college_address  Total Staff
c-001       vignan university  guntur           1200           1
c-002       RVR - JC           guntur           5644           1
c-004       Andhra University  guntur           670            1
c-021       vvit               guntur           3422           1
dtype: int64

From the above value_counts() in pandas example,

• we returned the count of each row by applying the value_counts() function on the entire dataframe.
• As each row appeared unique, so the value count for each row is 1.

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Example 2: value_counts in pandas example applied on column

In this value_counts on column pandas example, we will apply value_counts() on particular columns

import pandas as pd
from tabulate import tabulate

#create dataframe from the college data
data= pd.DataFrame({'college_id':['c-001','c-021','c-002','c-004'],

                    'college_name':["vignan university","vvit","RVR - JC","Andhra University"],

                   "college_address":["guntur","guntur","guntur","guntur"],

                    "Total Staff":['1200','3422','5644','670']

                   },index=['one','two','three','four'])

#display the dataframe by applying value_counts on college_address
print(data['college_address'].value_counts())

#display the dataframe by applying value_counts on college_name
print(data['college_name'].value_counts())

Output: value counts in pandas column result

guntur    4
Name: college_address, dtype: int64
vignan university    1
vvit                 1
RVR - JC             1
Andhra University    1
Name: college_name, dtype: int64

From the above value_counts() in pandas,

• we returned the count of each value from college_address and college_name column.
• As the value - guntur from college_address column occured 4 times.
• Hence the value counts for this column is 4 and the values occured unique in college_name column, so the value count is 1 for each value.

Thus we have learned how to apply value_counts on column pandas and entire dataframe by using value_counts in pandas dataframe.