python - Counting and printing zeroes and negative values for each Column in a Dataframe

Python - Counting and printing zeroes and negative values for each Column in a Dataframe

To count and print the number of zeroes and negative values for each column in a pandas DataFrame in Python, you can use the following approach:

import pandas as pd # Sample DataFrame data = { 'A': [1, 2, 0, -1], 'B': [-3, 0, 4, 0], 'C': [0, 0, 0, 0], 'D': [-2, -5, -3, -4] } df = pd.DataFrame(data) # Function to count zeroes and negative values for each column def count_zeros_negatives(column): zeroes = (column == 0).sum() negatives = (column < 0).sum() return zeroes, negatives # Iterate over columns and print counts for column in df.columns: zeroes, negatives = count_zeros_negatives(df[column]) print(f'Column {column}: Zeroes={zeroes}, Negatives={negatives}')

This code will output the counts of zeroes and negative values for each column in the DataFrame df.

Explanation:

  • We define a function count_zeros_negatives that takes a column as input, counts the number of zeroes and negative values using the sum() function along with boolean indexing, and returns the counts.
  • We iterate over each column in the DataFrame using df.columns.
  • For each column, we call the count_zeros_negatives function and print the counts along with the column name.

You can replace the sample DataFrame df with your actual DataFrame. This approach should work for any DataFrame with numerical columns.

Examples

  1. "Python pandas count zeros and negatives per column"

    • Description: This query aims to find a solution for counting the number of zero and negative values in each column of a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count zeros per column zeros_per_column = (df == 0).sum() # Count negatives per column negatives_per_column = (df < 0).sum() print("Zeros per column:") print(zeros_per_column) print("\nNegatives per column:") print(negatives_per_column)
    • Explanation: This code snippet creates a sample DataFrame and then utilizes pandas' built-in functionality to count the number of zero and negative values in each column.

  2. "Python pandas count zeroes and negatives in DataFrame"

    • Description: This query seeks a method to count the occurrences of zero and negative values within a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count zeros and negatives in DataFrame zeros_and_negatives_count = (df <= 0).sum().sum() print("Total count of zeros and negatives in DataFrame:", zeros_and_negatives_count)
    • Explanation: This code snippet calculates the total count of zero and negative values in the entire DataFrame by summing up the occurrences of such values in all columns.

  3. "Python pandas count zeros and negatives by column"

    • Description: This query looks for a solution to count the number of zero and negative values separately for each column in a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Function to count zeros and negatives by column def count_zeros_negatives(column): zeros = (column == 0).sum() negatives = (column < 0).sum() return zeros, negatives # Apply function to each column counts = df.apply(count_zeros_negatives) print("Counts of zeros and negatives per column:") print(counts)
    • Explanation: This code defines a function to count the number of zero and negative values in a single column, then applies this function to each column of the DataFrame, producing counts for each column.

  4. "Python pandas count zero values per column"

    • Description: This query specifically focuses on counting the occurrences of zero values in each column of a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count zero values per column zeros_per_column = (df == 0).sum() print("Zero values per column:") print(zeros_per_column)
    • Explanation: This code snippet utilizes the sum() function along with boolean indexing to count the occurrences of zero values in each column of the DataFrame.

  5. "Python pandas count negative values by column"

    • Description: This query aims to count the number of negative values in each column of a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count negative values per column negatives_per_column = (df < 0).sum() print("Negative values per column:") print(negatives_per_column)
    • Explanation: This code snippet uses boolean indexing to identify negative values in each column of the DataFrame and then sums them up to count the occurrences.

  6. "Python pandas count zeroes and negatives in DataFrame columns"

    • Description: This query looks for a method to count both zero and negative values within each column of a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count zeros and negatives in DataFrame columns counts = df.apply(lambda col: (col == 0).sum(), axis=0), df.apply(lambda col: (col < 0).sum(), axis=0) print("Counts of zeros and negatives per column:") print(counts)
    • Explanation: This code snippet utilizes the apply() function to apply custom lambda functions to each column, counting zero and negative values separately.

  7. "Python pandas count zeros and negatives in DataFrame by column"

    • Description: This query seeks a solution to count the occurrences of zero and negative values separately for each column in a pandas DataFrame.
    • Code:
      import pandas as pd # Sample DataFrame df = pd.DataFrame({'A': [1, 2, 0, -1], 'B': [0, 5, -2, 0], 'C': [-3, 0, 0, 4]}) # Count zeros and negatives in DataFrame by column counts = {'Zeros': (df == 0).sum(), 'Negatives': (df < 0).sum()} print("Counts of zeros and negatives per column:") print(counts)
    • Explanation: This code snippet calculates the counts of zero and negative values separately for each column and stores them in a dictionary.

More Tags

posts twitter-bootstrap-3 dbeaver viewbag do-while runtime activity-lifecycle spring-jms tokenize excel-2010

More Programming Questions

More Chemical reactions Calculators

More Fitness-Health Calculators

More Animal pregnancy Calculators

More Retirement Calculators