Python Pandas – Get the datatype and DataFrame columns information

To get the datatype and DataFrame columns information, use the info() method. Import the required library with an alias −

import pandas as pd;

Create a DataFrame with 3 columns −

dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'],"Place": ['Delhi','Bangalore','Hyderabad','Chandigarh','Pune', 'Mumbai', 'Jaipur'],"Units": [100, 150, 50, 110, 90, 120, 80] } ) 

Get the datatype and other info about the DataFrame −

dataFrame.info()

Example

Following is the code −

import pandas as pd; # create a DataFrame dataFrame = pd.DataFrame(    {       "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'],"Place": ['Delhi','Bangalore','Hyderabad','Chandigarh','Pune', 'Mumbai', 'Jaipur'],"Units": [100, 150, 50, 110, 90, 120, 80] } ) print"DataFrame ...\n",dataFrame # get unique values from a column print"\nUnique values from a column ...\n",dataFrame['Car'].unique() print"\nCount unique values from a column ...\n",dataFrame['Car'].nunique() # get datatype info print"\n Get the datatype info ...\n",dataFrame.info()

Output

This will produce the following output −

DataFrame ...        Car        Place   Units 0      BMW       Delhi     100 1     Audi   Bangalore     150 2      BMW   Hyderabad      50 3    Lexus  Chandigarh     110 4    Tesla        Pune      90 5    Lexus      Mumbai     120 6  Mustang      Jaipur      80 Unique values from a column ... ['BMW' 'Audi' 'Lexus' 'Tesla' 'Mustang'] Count unique values from a column ... 5 Get the datatype info ... RangeIndex: 7 entries, 0 to 6 Data   columns (total 3 columns): Car 7 non-null object Place 7 non-null object Units 7 non-null int64 dtypes: int64(1), object(2) memory usage: 240.0+ bytes None