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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
Updated on: 16-Sep-2021
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