Pandas: How to Check dtype for All Columns in DataFrame


You can use the following methods to check the data type (dtype) for columns in a pandas DataFrame:

Method 1: Check dtype of One Column

df.column_name.dtype

Method 2: Check dtype of All Columns

df.dtypes

Method 3: Check which Columns have Specific dtype

df.dtypes[df.dtypes == 'int64']

The following examples show how to use each method with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F'],
                   'points': [18, 22, 19, 14, 14, 11],
                   'assists': [5, 7, 7, 9, 12, 9],
                   'all_star': [True, False, False, True, True, True]})

#view DataFrame
print(df)

  team  points  assists  all_star
0    A      18        5      True
1    B      22        7     False
2    C      19        7     False
3    D      14        9      True
4    E      14       12      True
5    F      11        9      True

Example 1: Check dtype of One Column

We can use the following syntax to check the data type of just the points column in the DataFrame:

#check dtype of points column
df.points.dtype

dtype('int64')

From the output we can see that the points column has a data type of integer.

Example 2: Check dtype of All Columns

We can use the following syntax to check the data type of all columns in the DataFrame:

#check dtype of all columns
df.dtypes

team        object
points       int64
assists      int64
all_star      bool
dtype: object

From the output we can see:

  • team column: object (this is the same as a string)
  • points column: integer
  • assists column: integer
  • all_star column: boolean

By using this one line of code, we can see the data type of each column in the DataFrame.

Example 3: Check which Columns have Specific dtype

We can use the following syntax to check which columns in the DataFrame have a data type of int64:

#show all columns that have a class of int64
df.dtypes[df.dtypes == 'int64']

points     int64
assists    int64
dtype: object

From the output we can see that the points and assists columns both have a data type of int64.

We can use similar syntax to check which columns have other data types.

For example, we can use the following syntax to check which columns in the DataFrame have a data type of object:

#show all columns that have a class of object (i.e. string)
df.dtypes[df.dtypes == 'O']

team    object
dtype: object

We can see that only the team column has a data type of ‘O’, which stands for object.

Additional Resources

The following tutorials explain how to perform other common operations on pandas DataFrames:

Pandas: How to Get Cell Value from DataFrame
Pandas: Get Index of Rows Whose Column Matches Value
Pandas: How to Set Column as Index

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