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Pyspark: display a spark data frame in a table format
By default show () function prints 20 records of DataFrame. You can define number of rows you want to print by providing argument to show () function. You never know, what will be the total number of rows DataFrame will have. So, we can pass df.count () as argument to show function, which will print all records of DataFrame.
Stackoverflow.comShow distinct column values in pyspark dataframe
With pyspark dataframe, how do you do the equivalent of Pandas df['col'].unique(). I want to list out all the unique values in a pyspark dataframe column. Not the SQL type way (registertemplate then SQL query for distinct values). Also I don't need groupby then countDistinct, instead I want to check distinct VALUES in that column.
Stackoverflow.comPyspark: Filter dataframe based on multiple conditions
79. I want to filter dataframe according to the following conditions firstly (d<5) and secondly (value of col2 not equal its counterpart in col4 if value in col1 equal its counterpart in col3). If the original dataframe DF is as follows: The desired Dataframe is: Code I …
Stackoverflow.comComparison operator in PySpark (not equal/ !=) - Stack Overflow
Aug 24, 2016 · The selected correct answer does not address the question, and the other answers are all wrong for pyspark. There is no "!=" operator equivalent in pyspark for this solution. The correct answer is to use "==" and the "~" negation operator, like this:
Stackoverflow.comPyspark: explode json in column to multiple columns
Jun 28, 2018 · from pyspark.sql import functions as F df = df.select(F.col('a'), F.json_tuple(F.col('a'), 'k1', 'k2', 'k3') \ .alias('k1', 'k2', 'k3')) df.schema df.show(truncate=False) The document doesn't say much about it, but at least in my use case, new columns extracted by json_tuple are StringType , and it only extract single depth of JSON string.
Stackoverflow.compython - Concatenate two PySpark dataframes - Stack Overflow
May 20, 2016 · To make it more generic of keeping both columns in df1 and df2:. import pyspark.sql.functions as F # Keep all columns in either df1 or df2 def outter_union(df1, df2): # Add missing columns to df1 left_df = df1 for column in set(df2.columns) - set(df1.columns): left_df = left_df.withColumn(column, F.lit(None)) # Add missing columns to df2 right_df = df2 for column …
Stackoverflow.comPyspark: Parse a column of json strings - Stack Overflow
From pyspark.sql import functions as F # This one won't work for directly passing to from_json as it ignores top-level arrays in json strings # (if any)! # json_object_schema = spark_read_df.schema() # from_json is a bit more "simple", it directly applies the schema to the string.
Stackoverflow.comHow to change dataframe column names in PySpark?
You can use the following function to rename all the columns of your dataframe. def df_col_rename(X, to_rename, replace_with): """. :param X: spark dataframe. :param to_rename: list of original names. :param replace_with: list of new names. :return: dataframe with updated names. """. import pyspark.sql.functions as F.
Stackoverflow.compyspark - Apache spark dealing with case statements - Stack …
Jun 15, 2017 · Option#1: withColumn() using when-otherwise. Option#2: select() using when-otherwise. Option3: selectExpr() using SQL equivalent CASE expression. SQL like expression can also be written in withColumn() and select() using pyspark.sql.functions.expr function.
Stackoverflow.comPySpark: How to Append Dataframes in For Loop - Stack Overflow
May 29, 2019 · You should add, in your answer, the lines from functools import reduce from pyspark.sql import DataFrame So people don't have to look further up. – Laurent Commented Dec 2, 2021 at 13:09
Stackoverflow.com