In PySpark, we can drop one or more columns from a DataFrame using the .drop("column_name") method for a single column or .drop(["column1", "column2", ...]) for multiple columns. Jun 16, 2024 · 6 min read Cont
The pandasDataFrame.rename()function is a quite versatile function used not only to rename column names but also row indices. The good thing about this function is that you can rename specific columns. The syntax to change column names using the rename function. # Syntax to change column name...
It is possible to rename the columns of a Pandas pivot table using therename_axismethod. This method allows you to rename the levels of the columns and index of the DataFrame. Conclusion In this article, I have explained how to create a Panda pivot table with multiple columns involves using...
Select column Choose one or more columns to keep, and delete the rest Rename column Rename a column Drop missing values Remove rows with missing values Drop duplicate rows Drop all rows that have duplicate values in one or more columns Fill missing values Replace cells with missing values with...
# Rename columns for clarity df_cleaned = df_cleaned.select( col("countryOrRegion").alias("Country/Region"), col("holidayName").alias("Holiday Name"), col("normalizeHolidayName").alias("Normalized Holiday Name"), col("isPaidTimeOff").alias("Is Paid T...
object, (default ”) If the columns have multiple levels, determines how the other levels are named. If None then the index name is repeated. Returns DataFrame or None, DataFrame with the new index or None if inplace=True 1. How to reset the index? To reset the index in pandas, you...
2. How to plot a basic histogram in python? The pyplot.hist() in matplotlib lets you draw the histogram. It required the array as the required input and you can specify the number of bins needed. import matplotlib.pyplot as plt %matplotlib inline plt.rcParams.update({'figure.figsize':(7...
Suppose we have a DataFrame df with five columns: player_name, player_position, team, minutes_played, and score. The column minutes_played has many missing values, so we want to drop it. In PySpark, we can drop a single column from a DataFrame using the .drop() method. The syntax is...
Select column Choose one or more columns to keep, and delete the rest Rename column Rename a column Drop missing values Remove rows with missing values Drop duplicate rows Drop all rows that have duplicate values in one or more columns Fill missing values Replace cells with missing values with...
Now, let’s create a DataFrame with a few rows and columns, Our DataFrame contains column names Courses, Fee, Duration, and Discount. # Create a pandas DataFrame. import pandas as pd technologies = ({ 'Courses':["Spark","PySpark","Hadoop","Python","Pandas"], 'Fee' :[22000,25000,230...