Round each number in a Python pandas data frame by 2 decimals

Round each number in a Python pandas data frame by 2 decimals

You can round each number in a Pandas DataFrame to a specific number of decimal places using the .round() method. Here's how you can do it:

import pandas as pd # Create a sample DataFrame data = { 'A': [1.23456, 2.34567, 3.45678], 'B': [4.56789, 5.67890, 6.78901] } df = pd.DataFrame(data) # Round each number in the DataFrame to 2 decimal places rounded_df = df.round(2) print(rounded_df)

In this example, the .round(2) method is applied to the DataFrame df, rounding each number to 2 decimal places. The result will be a new DataFrame rounded_df with the rounded values.

Remember that the .round() method does not modify the original DataFrame but returns a new DataFrame with the rounded values. If you want to modify the original DataFrame, you can assign the result back to the original variable:

df = df.round(2)

Additionally, you can specify the number of decimal places individually for each column by providing a dictionary to the .round() method:

rounded_df = df.round({'A': 2, 'B': 3})

This will round column 'A' to 2 decimal places and column 'B' to 3 decimal places.

Examples

  1. "How to round a Pandas DataFrame to 2 decimal places in Python"

    • Description: This query explores rounding all numerical columns in a Pandas DataFrame to 2 decimal places.
    • Code:
      import pandas as pd df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890] }) # Round all numerical columns to 2 decimal places df_rounded = df.round(2) print(df_rounded) # Output: # A B # 0 1.23 4.57 # 1 2.35 5.68 # 2 3.46 6.79

  2. "Round specific columns in a Pandas DataFrame to 2 decimal places"

    • Description: This query discusses rounding only specific columns in a Pandas DataFrame to 2 decimal places.
    • Code:
      import pandas as pd df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890], 'C': ['X', 'Y', 'Z'] # Non-numeric column }) # Round only 'A' and 'B' columns to 2 decimal places df[['A', 'B']] = df[['A', 'B']].round(2) print(df) # Output: # A B C # 0 1.23 4.57 X # 1 2.35 5.68 Y # 2 3.46 6.79 Z

  3. "How to round DataFrame to 2 decimals with specific rounding method in Python"

    • Description: This query explores rounding with a specific method, like "round half up" to 2 decimal places.
    • Code:
      import pandas as pd import decimal from decimal import ROUND_HALF_UP decimal.getcontext().rounding = ROUND_HALF_UP # Set rounding method df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890] }) # Apply specific rounding method to all numerical columns df_rounded = df.applymap(lambda x: round(decimal.Decimal(x), 2)) print(df_rounded) # Output: # A B # 0 1.23 4.57 # 1 2.35 5.68 # 2 3.46 6.79

  4. "Round a Pandas Series to 2 decimal places"

    • Description: This query explores rounding a specific Pandas Series to 2 decimal places.
    • Code:
      import pandas as pd series = pd.Series([1.2345, 2.3456, 3.4567]) # Round the Series to 2 decimal places series_rounded = series.round(2) print(series_rounded) # Output: # 0 1.23 # 1 2.35 # 2 3.46 # dtype: float64

  5. "Round all numeric columns in a DataFrame to 2 decimal places in Pandas"

    • Description: This query discusses rounding all numeric columns in a DataFrame to 2 decimal places, ensuring non-numeric columns are unaffected.
    • Code:
      import pandas as pd df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890], 'C': ['X', 'Y', 'Z'] # Non-numeric column }) # Round only numeric columns to 2 decimal places df_rounded = df.select_dtypes(include=[float, int]).round(2) df.update(df_rounded) # Update DataFrame with rounded values print(df) # Output: # A B C # 0 1.23 4.57 X # 1 2.35 5.68 Y # 2 3.46 6.79 Z

  6. "Round a DataFrame with NaN values to 2 decimals in Pandas"

    • Description: This query discusses rounding down a DataFrame with NaN (Not-a-Number) values.
    • Code:
      import pandas as pd import numpy as np df = pd.DataFrame({ 'A': [1.2345, np.nan, 3.4567], 'B': [4.5678, 5.6789, np.nan] }) # Round numeric columns to 2 decimal places, NaN values stay unchanged df_rounded = df.round(2) print(df_rounded) # Output: # A B # 0 1.23 4.57 # 1 NaN 5.68 # 2 3.46 NaN

  7. "Round a DataFrame to 2 decimals and export to CSV in Pandas"

    • Description: This query explores rounding a DataFrame and then exporting the result to a CSV file.
    • Code:
      import pandas as pd df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890] }) # Round to 2 decimals df_rounded = df.round(2) # Export to CSV df_rounded.to_csv('rounded_output.csv', index=False)

  8. "Round DataFrame with a specified rounding mode to 2 decimals in Pandas"

    • Description: This query discusses rounding with a specified rounding mode, such as "ROUND_HALF_DOWN."
    • Code:
      import pandas as pd import decimal from decimal import ROUND_HALF_DOWN decimal.getcontext().rounding = ROUND_HALF_DOWN df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890] }) # Apply specific rounding mode to all numerical columns df_rounded = df.applymap(lambda x: round(decimal.Decimal(x), 2)) print(df_rounded)

  9. "Round DataFrame with conditional rounding to 2 decimals in Pandas"

    • Description: This query explores conditional rounding, where certain conditions affect how numbers are rounded.
    • Code:
      import pandas as pd df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890] }) # Conditional rounding: only round values above 2.5 df_rounded = df.applymap(lambda x: round(x, 2) if x > 2.5 else x) print(df_rounded) # Output: # A B # 0 1.2345 4.57 # 1 2.3456 5.68 # 2 3.46 6.79

  10. "Round DataFrame using custom rounding function to 2 decimals in Pandas"

    • Description: This query explores applying a custom rounding function to round values to 2 decimal places in Pandas.
    • Code:
      import pandas as pd # Custom rounding function def custom_round(x): return round(x, 2) if isinstance(x, float) else x df = pd.DataFrame({ 'A': [1.2345, 2.3456, 3.4567], 'B': [4.5678, 5.6789, 6.7890], 'C': ['X', 'Y', 'Z'] # Non-numeric column }) # Apply custom rounding function df_rounded = df.applymap(custom_round) print(df_rounded) # Output: # A B C # 0 1.23 4.57 X # 1 2.35 5.68 Y # 2 3.46 6.79 Z

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