Pyspark dataframe select columns dynamically. . This is a very easy method, and I use it frequently when arranging features into vectors for machine learning tasks. functions module plays a key role in referencing and manipulating DataFrame columns dynamically. Let’s explore these approaches with examples across common operations, such as filtering, selecting, and applying transformations. Unlike SQL, PySpark provides several options for referring to columns, each suited to different tasks. Returns DataFrame A DataFrame with subset (or all) of columns. Here are some common approaches: Using the select () method: The select() method allows you to specify the columns you want to select by passing the column names as arguments. from_catalog( This section introduces the most fundamental data structure in PySpark: the DataFrame. In PySpark, there are multiple ways to select columns from a DataFrame. Aug 5, 2020 · How to select columns using dynamic select query using window function Asked 4 years, 9 months ago Modified 4 years, 9 months ago Viewed 847 times I have a vast amount of raw delta tables in Databricks (bronze), and I want to clean them up by only selecting a few columns and renaming them appropriately (before saving them to a new database; s May 12, 2024 · Conclusion Remember, the `select ()` function in PySpark DataFrame creates a new DataFrame with the specified columns or transformations. A DataFrame is a two-dimensional labeled data structure with columns of potentially different types. Alternatively, you can rearrange columns using df[column_order], where column_order is a list of column names in the desired order. Whether you’re trimming datasets to the essentials, crafting new columns with a bit of math, or renaming fields for clarity, select is how you get it done. Apr 14, 2021 · I have a Dataframe and I want to dynamically pass the columns names through widgets in a select statement in my Databricks Notebook. Mar 27, 2024 · Use PySpark withColumnRenamed() to rename a DataFrame column, we often need to rename one column or multiple (or all) columns on PySpark DataFrame, you can do this in several ways. fromDF(dataframe, glue_ctx, name) Converts a DataFrame to a DynamicFrame by converting DataFrame fields to DynamicRecord fields. The struct fields (properties) are optional so I want to construct the select statement based on input data. Select columns in PySpark dataframe – A Comprehensive Guide to Selecting Columns in different ways in PySpark dataframe Join thousands of students who advanced their careers with MachineLearningPlus. It is similar to a row in a Spark DataFrame, except that it is self-describing and can be used for data that does not conform to a fixed schema. This function expects columns In PySpark, referencing columns is essential for filtering, selecting, transforming, and performing other DataFrame operations. columns I would like to read columns dynamically from MetaData. This tutorial will outline various methods for selecting columns, providing flexibility in how you manipulate and view your data. Schema Inferred with : Parameters colsstr, Column, or list column names (string) or expressions (Column). select('time Nov 28, 2023 · PySpark, the Python API for Apache Spark, provides a robust framework for large-scale data processing. May 17, 2023 · I have a table called MetaData and what columns are needed in the select are stored in MetaData. The 2nd dataframe contains certain name of the columns from 1st dataframe. sql("SELECT column1, column2 FROM your_db_name. In this article, I will explain how to reorder columns in a specific order using Polars. Examples Aug 19, 2025 · In this PySpark article, you will learn how to apply a filter on DataFrame columns of string, arrays, and struct types by using single and multiple Aug 19, 2025 · In this PySpark article, you will learn how to apply a filter on DataFrame columns of string, arrays, and struct types by using single and multiple Oct 18, 2018 · Dynamically passing Query String for selecting columns in PySpark Dataframe method selectExpr () Asked 6 years, 10 months ago Modified 2 years, 11 months ago Viewed 4k times # Read from the customers table in the glue data catalog using a dynamic frame and convert to spark dataframe dfOrders = glueContext. your_table_name WHERE column1 = ?", args=['some_value']) Parameterized SQL does not allow for a way to replace database, table names, or column names. Understanding how to work with columns is essential for manipulating and transforming data efficiently. csv_values = "col1, col2, col3, col4" df = spark. Oct 31, 2022 · I have columns in my dataframe df1 like this where the columns starting with 20 were generated dynamically. ) that allow Jun 29, 2021 · In this article, we are going to select columns in the dataframe based on the condition using the where () function in Pyspark. You can think of a DataFrame like a spreadsheet, a SQL table, or a dictionary of series objects. import org. Apr 16, 2018 · 0 I am trying to infer the schema for struct and constructing a list which contain struct fields (enclosed with col , replaced : with _ as alias name) in the select column list of dataframe. createDataFrame([(csv_values,)], ["csv_column"]) Aug 9, 2017 · I often need to perform an inverse selection of columns in a dataframe, or exclude some columns from a query. How can I do it? I am using the below code df1 = spark. I want to append a new column to the dataframe based on the following logic - for every row, one of the "name_" columns contains the string "Standard". Apr 17, 2025 · The primary method for selecting specific columns from a PySpark DataFrame is the select () method, which creates a new DataFrame with the specified columns. The col() function from the pyspark. When columns are nested it becomes complicated. create_dynamic_frame. Returns the new DynamicFrame. May 2, 2023 · 0 I have a PySpark dataframe that contains dynamic number of columns - auto_id, val0, name0, val1, name1,. spark. sql(" Dec 23, 2023 · Explore efficient techniques for renaming DataFrame columns using PySpark withcolumnrenamed. Mar 10, 2025 · In Polars, you can use the select() function to reorder columns in a specific order, allowing you to explicitly define the desired column sequence for your DataFrame. 4, you can now add positional parameters: spark. Let's create a sample dataframe with employee data. columns = ['home','house','office','work'] #select the list of columns df_tables_full. This immutability aligns with the functional programming Select Operation in PySpark DataFrames: A Comprehensive Guide PySpark’s DataFrame API is your go-to for big data, and the select operation is the trusty tool you’ll use to shape it. Jan 31, 2023 · I have a dataframe with multiple columns as t_orno,t_pono, t_sqnb ,t_pric,. com In PySpark, selecting columns from a DataFrame is a crucial operation that resembles the SQL SELECT statement. The original DataFrame remains unchanged. I could rename the columns starting with 20 to 2019_p, 2020_p, 2021_p dynamically using df. Apache Spark DataFrames support a rich set of APIs (select columns, filter, join, aggregate, etc. A DynamicRecord represents a logical record in a DynamicFrame. Optimize your PySpark code with these strategies for improved performance. Sep 14, 2024 · Let’s say you want to dynamically select and rename multiple columns in a DataFrame. Sep 25, 2019 · The documentation for PySpark's SQL command shows that, starting in version 3. and so on (it's a table with multiple columns). select. columns and create a view based on that. You can pass column names as strings, col () expressions, or column objects, and even include expressions for computed columns. The * operator can be used to unpack the columns, and with the help of withColumnRenamed(), you can rename See full list on sparkbyexamples. apache. , valxx, namexx (where xx is dynamic, but less than 100). Use * before columns to unnest columns list and use in . Unlike traditional pandas DataFrames, PySpark DataFrames are immutable, meaning any operation on them creates a new DataFrame rather than modifying the existing one. Learn to rename single and multiple columns, handle nested structures, and dynamically rename columns. Go from Beginner to Data Science (AI/ML/Gen AI) Expert through a structured pathway of 9 core specializations and build industry grade projects. sql. If one of the column names is ‘*’, that column is expanded to include all columns in the current DataFrame. Column // Create an example dataframe Dec 22, 2023 · Introduction to PySpark DataFrame Operations PySpark Select Columns One of its key features is the DataFrame, a distributed collection of data organized into named columns. xh9qx cj 42bdma 8a5 0v5y1 gmvn 5hj00h 6tu bhen usnq9