CLASS 12 DATAFRAME ATTRIBUTES

 

Introduction

A DataFrame in pandas is a two-dimensional labeled data structure with columns of potentially different types. It's similar to a table in a database or a data frame in R. Understanding DataFrame attributes is crucial for effective data manipulation and analysis.

Common DataFrame Attributes

1. .shape

   • Returns a tuple representing the dimensionality of the DataFrame.
   • Example:

     
     df.shape
     

2. .size

   • Returns the number of elements in the DataFrame.
   • Example:

     
     df.size
     

3. .ndim

   • Returns the number of dimensions of the DataFrame.
   • Example:

     
     df.ndim
     

4. .dtypes

   • Returns the data types of each column.
   • Example:

     df.dtypes
     

5. .columns

   • Returns the column labels of the DataFrame.
   • Example:

     
     df.columns
     

6. .index

   • Returns the row labels of the DataFrame.
   • Example:

     df.index
     

7. .values

   • Returns the underlying data of the DataFrame as a NumPy array.
   • Example:

     
     df.values
     

Examples

Let's consider the following DataFrame for examples:

import pandas as pd

data = {
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [24, 27, 22],
    'Salary': [70000, 80000, 65000]
}

df = pd.DataFrame(data)

1. .shape

   
   print(df.shape)  # Output: (3, 3)
   

2. .size

   
   print(df.size)  # Output: 9
   

3. .ndim

   print(df.ndim)  # Output: 2
   

4. .dtypes

   print(df.dtypes)  
   # Output:
   # Name      object
   # Age        int64
   # Salary     int64
   # dtype: object
   

5. .columns

   
   print(df.columns)  
   # Output: Index(['Name', 'Age', 'Salary'], dtype='object')
   

6. .index

   
   print(df.index)  
   # Output: RangeIndex(start=0, stop=3, step=1)
   

7. .values

   
   print(df.values)  
   # Output:
   # [['Alice' 24 70000]
   #  ['Bob' 27 80000]
   #  ['Charlie' 22 65000]]

8. import pandas as pd

   
   

   data = {'col1': [1, 2], 'col2': [3, 4]}

   df = pd.DataFrame(data)

   df_transpose = df.transpose()

   df_transpose_attr = df.T

   print("Dataframe:")

   print(df)

   print("Transpose using transpose() method:")

   print(df_transpose)

   print("Transpose using 'T'")

   print(df_transpose_attr)

         

Dataframe attributes list Attributes of dataframe Class 12 Pandas DataFrame attributes list Dataframe attributes pdf Dataframe attributes examples Pandas attributes and methods DataFrame' object has no attribute 'append Which attribute of data frame is used to retrieve its shape