Pandas - Ensure no negative values in a DataFrame column
15. Ensuring No Negative Values in a DataFrame Column
Write a Pandas program that ensures no negative values in a DataFrame column.
This exercise shows how to ensure that a column contains no negative values.
Sample Solution :
Code :
import pandas as pd
# Create a sample DataFrame with numerical values
df = pd.DataFrame({
'Amount': [100, -50, 200, -10]
})
# Check for any negative values in the 'Amount' column
no_negatives = (df['Amount'] >= 0).all()
# Output the result
print(f"Are there any negative values? {not no_negatives}")
Output:
Are there any negative values? True
Explanation:
- Created a DataFrame with numerical 'Amount' values, including negatives.
- Used a condition to check if all values in the 'Amount' column are non-negative.
- Outputted whether there are any negative values in the column.
For more Practice: Solve these Related Problems:
- Write a Pandas program to check that a specific numeric column contains no negative values and list any violations.
- Write a Pandas program to replace negative values in a DataFrame column with zero and validate the change.
- Write a Pandas program to flag rows in which a numeric column has negative values and export those rows for further analysis.
- Write a Pandas program to validate numeric columns by ensuring no negative values exist and compute summary statistics for flagged rows.
Python-Pandas Code Editor:
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