How to count rows in a pandas DataFrame [Practical Examples]

Different methods to count rows in pandas DataFrame

In this tutorial we will discuss how to count rows in panads dataframe  using the following methods:

• Using axes() function
• Using shape() function
• Using index
• Using info() method
• Using len() function
• Using count() function
• Using value_counts() function

 

Create pandas DataFrame with example data

DataFrame is a data structure used to store the data in two dimensional format. It is similar to table that stores the data in rows and columns. Rows represents the records/ tuples and columns refers to the attributes.

We can create the DataFrame by using pandas.DataFrame() method.

Syntax:

pandas.DataFrame(input_data,columns,index)

Parameters:

It will take mainly three parameters

1. input_data is represents a list of data
2. columns represent the columns names for the data
3. index represent the row numbers/values

We can also create a DataFrame using dictionary by skipping columns and indices.

 

Example: Python Program to create a dataframe for market data from a dictionary of food items by specifying the column names.

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# display the dataframe
print(dataframe)

Output:

            id            name    cost  quantity
item-1  foo-23  ground-nut oil  567.00         1
item-2  foo-13         almonds  562.56         2
item-3  foo-02           flour   67.00         3
item-4  foo-31         cereals   76.09         2

 

Method 1 : count rows in pandas DataFrame using axes() function

Here we are going to display the count of total number of rows available in pandas dataframe. So we are using axes() function to get the count inside the  len() function. It will get the length of rows

we have to specify index - 0 inside this function to get row count.

Syntax:

len(dataframe.axes[0])

where,

1. dataframe is the input dataframe
2. [0] specifies the row

 

Example: In this program we are going to get the count the rows from the above dataframe

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(len(dataframe.axes[0]))

Output:

4

 

Method 2 : count rows in pandas DataFrame using shape() function

Here we are going to display the count of total number of rows available in pandas dataframe. So we are using shape() function to get the count. shape() will return number of rows and number of columns from the given dataframe. If we want to get the number of rows, we have to specify index - 0 inside this function to get row count.

Syntax:

dataframe.shape[0]

where,

1. dataframe is the input dataframe
2. [0] specifies the row

 

Example 1: In this program we are going to get the count the rows from the above dataframe

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(dataframe.shape[0])

Output:

4

If we want to get the count of rows and columns , then we have to simply use shape.

 

Example 2: In this program we are going to get the count the rows and columns from the above dataframe

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows and columns from the  dataframe
print(dataframe.shape)

Output:

(4, 4)

 

Method 3 : count rows in pandas DataFrame using index

Here we are going to display the count of total number of rows available in pandas dataframe. So we are using index function to get the row inside with len() function

Syntax:

len(dataframe.index)

where, dataframe is the input dataframe

 

Example: In this program we are going to get the count the rows from the above dataframe

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(len(dataframe.index))

Output:

4

 

Method 4 : count rows in pandas DataFrame using info() method

info() is used to get the total rows along with columns names and its data types. It will retunr the class type i.e the Pandas DataFrame , data types of the each column by displaying the column name with non null vales count. Atlast it will return the size of memory utilized.

Syntax:

dataframe.info()

where, dataframe is the input dataframe

 

Example: Python program to get the row count with info() method

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(dataframe.info())

Output:

<class 'pandas.core.frame.DataFrame'>
Index: 4 entries, item-1 to item-4
Data columns (total 4 columns):
 #   Column    Non-Null Count  Dtype  
---  ------    --------------  -----  
 0   id        4 non-null      object 
 1   name      4 non-null      object 
 2   cost      4 non-null      float64
 3   quantity  4 non-null      int64  
dtypes: float64(1), int64(1), object(2)
memory usage: 160.0+ bytes
None

 

Method 5 : count rows in pandas DataFrame using len() function

In this scenario, we will be using len() function to get the total number of rows from the pandas dataframe

Syntax:

len(dataframe)

where, dataframe is the input dataframe

 

Example: Python program to get the count of rows using len() function

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(len(dataframe))

Output:

4

 

Method 6 : count rows in pandas DataFrame using count() function

Here we have to use count() function inorder to get the count of total rows in the pandas dataframe. It will return the count in all columns and display column wise.

Syntax:

DataFrame.count(axis=0, level=None, numeric_only=False)

where,

1. dataframe is the input dataframe.
2. axis: If 0 or ‘index’ counts are generated for each column. If 1 or ‘columns’ counts are generated for each row.
3. level: If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a DataFrame. A str specifies the level name.
4. numeric_only: Include only float, int or boolean data.

 

Example: Python program to use count() function to return the number of rows across all columns

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(dataframe.count())

Output:

id          4
name        4
cost        4
quantity    4
dtype: int64

 

Method 7 : count rows in pandas DataFrame using value_counts() function

value_counts() function is used count of row occurrence across the columns in the pandas dataframe. It will return the row and columns along with count of occurrence. This function will return the count of each row at the  end of each row.

Syntax:

DataFrame.value_counts(subset=None, normalize=False, sort=True, ascending=False, dropna=True)

where,

1. subset:  Columns to use when counting unique combinations.
2. normalize: Return proportions rather than frequencies.
3. sort: Sort by frequencies.
4. ascending: Sort in ascending order.
5. dropna: Don’t include counts of rows that contain NA values.

 

Example: Python program to count rows using value_counts()

# import the module
import pandas

# consider the food data
food_input={'id':['foo-23','foo-13','foo-02','foo-31'],
                  'name':['ground-nut oil','almonds','flour','cereals'],
                  'cost':[567.00,562.56,67.00,76.09],
                  'quantity':[1,2,3,2]}

# pass this food to the dataframe by specifying rows 
dataframe=pandas.DataFrame(food_input,index = ['item-1', 'item-2', 'item-3', 'item-4'])

# count the rows from the  dataframe
print(dataframe.value_counts())

Output:

id      name            cost    quantity
foo-31  cereals         76.09   2           1
foo-23  ground-nut oil  567.00  1           1
foo-13  almonds         562.56  2           1
foo-02  flour           67.00   3           1
dtype: int64

 

Summary

In this tutorial we discussed how to count rows from the dataframe using axes,shape,len,count,value_counts(),index and info() functions. We have used len() function in functions like axes and index. Finally, we also observed that by using info() and value_counts() functions  will return other information related to the dataframe other than row count.

 

Reference

• Pandas - count()