To retrieve individual cell values or select rows based on a category in a DataFrame, you can use Pandas, a popular Python library for data manipulation. Here's how you can achieve this:

1. Retrieve an Individual Cell Value

To access an individual cell, you can use the .loc[] or .iloc[] methods: - .loc[]: Selects data by label. - .iloc[]: Selects data by position.

```python import pandas as pd

Example DataFrame

data = { 'Category': ['A', 'B', 'A', 'C'], 'Value': [10, 20, 15, 30] } df = pd.DataFrame(data)

Retrieve a specific cell (e.g., the value in the second row, 'Value' column)

cell_value = df.loc[1, 'Value'] # Select by row index and column name print("Cell Value:", cell_value) ```

2. Select Rows Based on a Category

You can filter rows based on a specific category using a boolean mask.

```python

Select rows where the 'Category' column equals 'A'

filtered_rows = df[df['Category'] == 'A'] print(filtered_rows) ```

3. Retrieve a Cell Value from Filtered Rows

You can combine filtering and retrieval.

```python

Get the 'Value' column for rows where 'Category' is 'A'

specific_value = df[df['Category'] == 'A'].iloc[0]['Value'] print("Specific Value:", specific_value) ```

Example Output

For the above code:

DataFrame

| | Category | Value | |---|----------|-------| | 0 | A | 10 | | 1 | B | 20 | | 2 | A | 15 | | 3 | C | 30 |

Output

plaintext Cell Value: 20 Category Value 0 A 10 2 A 15 Specific Value: 10

Let me know if you need further assistance!