How to search a value within a Pandas DataFrame row?

Pandas DataFrame is a two-dimensional data structure that represents data in tabular form with rows and columns. Python provides several built-in methods like eq(), any(), loc[], and apply() to search for specific values within DataFrame rows.

Basic Value Search in a Column

The simplest approach is to search for a value in a specific column using boolean indexing ?

import pandas as pd

# Create a DataFrame
data = {'Name': ['Bhavish', 'Abhinabh', 'Siddhu'],
        'Age': [25, 32, 28]}
df = pd.DataFrame(data)

# Search for a value in the 'Name' column
search_value = 'Siddhu'
result = df[df['Name'] == search_value]
print(result)

     Name  Age
2  Siddhu   28

Search Across All Columns Using eq() and any()

To search for a value across all columns in a DataFrame, combine eq() with any(axis=1) ?

import pandas as pd

# Create a DataFrame
data = {'Name': ['A', 'X', 'C', 'F', 'L', 'G'],
        'Age': [25, 32, 18, 29, 13, 19]}
df = pd.DataFrame(data)

# Search for a value across all columns
search_value = 'F'
result = df[df.eq(search_value).any(axis=1)]
print(result)

  Name  Age
3    F   29

Search Within Specific Column Range Using loc[]

Use loc[] to search within a specific range of columns ?

import pandas as pd

# Create a DataFrame
data = {'Name': ['Shyam', 'Ranjan', 'Mohan', 'Raju', 'Dheeraj'],
        'Age': [25, 32, 18, 22, 26],
        'Designation': ['SDE', 'Tester', 'Web Developer', 'Intern', 'HR'],
        'Salary': [50000, 17000, 26000, 20000, 17000]}
df = pd.DataFrame(data)

# Search for a value within a range of columns
search_value = 17000
result = df.loc[df.loc[:, 'Age':'Salary'].eq(search_value).any(axis=1)]
print(result)

     Name  Age Designation  Salary
1  Ranjan   32      Tester   17000
4  Dheeraj   26          HR   17000

Search Using apply() and Lambda

The apply() function with a lambda expression provides flexible row-wise searching ?

import pandas as pd

# Create a simple DataFrame
data = {"Name": ["Keshav", "Vishal", "Aman", "Shubham", "Amar"],
        "Age": [23, 22, 24, 26, 21]}
df = pd.DataFrame(data)

# Search for the value 22 in all rows using apply() and lambda
search_value = 22
if df.apply(lambda row: search_value in row.values, axis=1).any():
    print(f"{search_value} found in at least one row")
else:
    print(f"{search_value} not found in any row")

22 found in at least one row

Method Comparison

Conclusion

Use boolean indexing for simple column searches, eq().any(axis=1) for searching across all columns, and apply() with lambda for complex conditions. Choose the method based on your specific search requirements and performance needs.