Pandas Retrieve Number of Columns

To retrieve the number of columns in a Pandas DataFrame, you can use the shape attribute, which returns a tuple representing the dimensions of the DataFrame. The first element of the tuple is the number of rows, and the second element is the number of columns.

In this article, I will explain how to retrieve the number of columns by using axes(), len(), shape(), and info() functions with examples.

Key Points –

• Use the shape attribute of a Pandas DataFrame to retrieve the number of columns.
• shape returns a tuple representing the dimensions of the DataFrame, where the first element denotes the number of rows and the second element denotes the number of columns.
• Access the number of columns by indexing the second element of the tuple returned by shape.
• The number of columns can also be obtained using the len() function on the DataFrame’s columns attribute.

Related: Get All Header Columns from pandas DataFrame

Quick Examples of Retrieve Number of Columns

Following are quick examples of retrieving number columns.

# Quick examples of retrieve number columns 

# Using df.axes() method 
# To get number columns
cols = len(df.axes[1])
count = str(cols)

# Using DataFrame.len() method 
count = len(df.columns)

# Get the number of columns and rows
shape = df.shape

# Using DataFrame.shape method
count = df.shape[1]

# Using DataFrame.info() method 
df.info()

To run some examples of retrieving number columns, let’s create Pandas DataFrame using data from a dictionary.

# Create DataFrame
import pandas as pd
technologies = {
    'Courses':["Spark","PySpark","Python","pandas","Hadoop"],
    'Fee' :[20000,25000,22000,24000,30000],
    'Duration':['30days','40days','35days','60days','50days'],
    'Discount':[1000,2300,2500,2000,3000]
              }
index_labels=['r1','r2','r3','r4','r5']
df = pd.DataFrame(technologies,index=index_labels)
print(df)

Yields below output.

# Output:
    Courses    Fee Duration  Discount
r1    Spark  20000   30days      1000
r2  PySpark  25000   40days      2300
r3   Python  22000   35days      2500
r4   pandas  24000   60days      2000
r5   Hadoop  30000   50days      3000

Retrieve Number Columns using DataFrame.axes()

You can retrieve the number of columns in a Pandas DataFrame using the axes attribute. The axes attribute returns a list of axis labels, where the first element represents the row axis labels and the second element represents the column axis labels. To get the number of columns, you can use the len() function on the second element of the axes list.

# Using df.axes() method 
# To get number of columns
cols = len(df.axes[1])
count = str(cols)
print("Get number of Columns: " + count)

Yields below output.

# Output:
Get number of Columns: 4

Using DataFrame.len() Method

Alternatively, you can also retrieve the number of columns in a DataFrame using the len() function with the columns attribute.

# Using DataFrame.len() method 
count = len(df.columns)
print("Get number of Columns:", count)

# Output:
# Get number of Columns: 4

In the above examples, len(df.columns) gets you the number of columns. Here, the df.columns return the DataFrame column names as a list.

Using DataFrame.shape() Method

Similarly, to retrieve the number of columns in a DataFrame using the shape method, you can access the second element of the tuple returned by shape, which represents the number of columns.

# Get the number of columns and rows
df.shape

# Using DataFrame.shape[1]
# To get columns count
columns_count = df.shape[1]
print("Get number of Columns:", columns_count)

# Output:
# Get number of Columns: 4

Using DataFrame.info() Method

The info() method in Pandas provides a concise summary of the DataFrame, including information about the number of columns. You can use it to quickly retrieve the number of columns.

# Using DataFrame.info() method 
df.info()

This method will display information about the DataFrame, including the number of columns and their data types, non-null values, and memory usage.

# Output:
<class 'pandas.core.frame.DataFrame'>
Index: 5 entries, r1 to r5
Data columns (total 4 columns):
 #   Column    Non-Null Count  Dtype 
---  ------    --------------  ----- 
 0   Courses   5 non-null      object
 1   Fee       5 non-null      int64 
 2   Duration  5 non-null      object
 3   Discount  5 non-null      int64 
dtypes: int64(2), object(2)
memory usage: 200.0+ bytes

Complete Example

import pandas as pd
technologies = {
    'Courses':["Spark","PySpark","Python","pandas","Hadoop"],
    'Fee' :[20000,25000,22000,24000,30000],
    'Duration':['30days','40days','35days','60days','50days'],
    'Discount':[1000,2300,2500,2000,3000]
              }
index_labels=['r1','r2','r3','r4','r5']
df = pd.DataFrame(technologies,index=index_labels)
print(df)

# Using df.axes() method 
# To get number columns
cols = len(df.axes[1])
count = str(cols)
print("Get number of Columns: " + count)

# Using DataFrame.len() method 
count = len(df.columns)
print("Get number of Columns:", count)

# Using DataFrame.shape method
count = df.shape[1]
print("Get number of Columns:", count)

# Get the number of columns and rows
shape = df.shape
print(shape)

# Using DataFrame.info() method 
df.info()

Frequently Asked Questions on Retrieve Number of Columns

Conclusion

In this article, I have explained retrieve the number of columns from DataFrame using axes(), len(), shape() and info() functions with examples. When you use the shape, use the shape[1] to retrieve the number of columns.

Happy Learning !!

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• Change Column Data Type On Pandas DataFrame
• Drop Single & Multiple Columns From Pandas DataFrame
• Pandas Delete DataFrame Rows Based on Column Value

References

• https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.get.html