Python Pandas – How to select DataFrame rows on the basis of conditions

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We can set conditions and fetch DataFrame rows. These conditions can be set using logical operators and even relational operators.

At first, import the required pandas libraries −

import pandas as pd

Let us create a DataFrame and read our CSV file −

dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\SalesRecords.csv")

Fetching dataframe rows with registration price less than 1000. We are using relational operator for this −

dataFrame[dataFrame.Reg_Price < 1000]

Example

Following is the code −

import pandas as pd

# reading csv file
dataFrame = pd.read_csv("C:\\Users\\amit_\\Desktop\\SalesRecords.csv")
print("DataFrame...\n",dataFrame)

# count the rows and columns in a DataFrame
print("\nNumber of rows and column in our DataFrame = ",dataFrame.shape)

# fetching dataframe rows with registration price less than 1000
resData = dataFrame[dataFrame.Reg_Price < 1000]

print("DataFrame...\n",resData)

Output

This will produce the following output −

DataFrame...
           Car   Date_of_Purchase   Reg_Price
0          BMW         10/10/2020        1000
1        Lexus         10/12/2020         750
2         Audi         10/17/2020         750
3       Jaguar         10/16/2020        1500
4      Mustang         10/19/2020        1100
5  Lamborghini         10/22/2020        1000

Number of rows and column in our DataFrame = (6, 3)
DataFrame...
     Car   Date_of_Purchase   Reg_Price
1  Lexus         10/12/2020         750
2   Audi         10/17/2020         750
raja
Published on 28-Sep-2021 11:01:52
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