pandas DataFrame Filtering

Learn to perform the filtering operation on a pandas DataFrame.

python

# Importing the pandas library as pd
import pandas as pd

# Creating a Python Dictionary
dictionary = {
    "Fruit": ["Apple", "Orange", "Mango"],
    "Weight": ["1kg", "2kg", "5kg"],
    "Price": [300, 150, 800],
}

# Creating a Pandas DataFrame
df = pd.DataFrame(dictionary)

# Printing the DataFrame
print(df)

You can call the filter() method from a pandas DataFrame to select a subset of the original dataframe according to the specified index labels.

python

# Selecting Fruit and Weight columns
print(df.filter(items=["Fruit", "Weight"]))

python

# Selecting specific columns
print(df[["Fruit", "Weight"]])

Selecting rows using conditional statements,

python

# Specifying a conditional statement
print(df["Price"] == 300)

# Selecting rows that satisfy a conditional statement
print(df[df["Price"] == 300])

python

# Selecting rows that satisfy multiple conditional statements
print(df[(df["Price"] == 300) | (df["Price"] < 300)])

You can also select specific rows using the isin() method,

python

print(df['Fruit'].isin(['Apple', 'Orange']))
print(df[df['Fruit'].isin(['Apple', 'Mango'])])