How to search a value within a ROW of a Pandas DataFrame in Python

Searching for a specific value within a Pandas DataFrame in Python can be done by using the .loc[] or .iloc[] functions. These functions allow you to select specific rows and columns from a DataFrame based on their labels or indices.

First, you need to import the Pandas library and create a DataFrame. For example, you can create a DataFrame with some sample data.

import pandas as pd

data = {'product': ['Apple', 'Banana', 'Cherry', 'Date', 'Eggplant'],

'price': [1.2, 2.3, 2.5, 1.7, 2.0],

'quantity': [3, 5, 2, 4, 8]}

df = pd.DataFrame(data)

Next, you can use the .loc[] or .iloc[] functions to search for a specific value within the DataFrame. The .loc[] function allows you to select rows and columns by their labels, while the .iloc[] function allows you to select rows and columns by their indices.

For example, if you want to search for the value ‘Banana’ in the ‘product’ column, you can use the following code with .loc[] function:

df.loc[df['product'] == 'Banana']

Or you can use the following code with .iloc[] function:

df.iloc[df.index[df['product'] == 'Banana'].tolist()]

By using .loc[] or .iloc[] functions, you can easily search for a specific value within a Pandas DataFrame in Python. This can be useful for data analysis, as it allows you to select specific rows and columns based on their values. It can also be used for exploring and filtering data in an organized manner.

Let’s check the following example in Python:

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How to search a value within a Pandas DataFrame in Python

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