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Tag: pyspark

How I can select a column where in another column I need a specific things

I have a pyspark data frame. How I can select a column where in another column I need a specific things. suppose I have n columns. for 2 columns I have A. B. a b a c d f I want all column B. …

Converting query from SQL to pyspark

I am trying to convert the following SQL query into pyspark: The code I have in PySpark right now is this: However, this is simply returning the number of rows in the “data” dataframe, and I know this isn’t correct. I am very new at PySpark, can anyone help me solve this? Answer You need to collect the result into

How do I specify a default value when the value is “null” in a spark dataframe?

I have a data frame like the picture below. In the case of “null” among the values of the “item_param” column, I want to replace the string’test’. How can I do it? df = sv_df….

How to add a ranking to a pyspark dataframe

I have a pyspark dataframe with 2 columns – id and count. I want to add a ranking to this by reverse count. So the highest count has rank 1, second highest rank 2, etc. testDF = spark.createDataFrame([(DJS232,437232)], [“id”, “count”]) I first tried using and this worked, ish. It had monotonically increasing id numbers but the jump from the first

Groupby fill missing values in dataframe based on average of previous values available and next value available

I have data frame which has some groups and I want to fill the missing values based on last previous available and next value available average of score column i.e. (previous value+next value)/2. I …

Filtering rows in pyspark dataframe and creating a new column that contains the result

so I am trying to identify the crime that happens within the SF downtown boundary on Sunday. My idea was to first write a UDF to label if each crime is in the area I identify as the downtown area, if …

Is there a way to compare all rows in one column of a dataframe against all rows in another column of another dataframe (spark)?

I have two dataframes in Spark, both with an IP column. One column has over 800000 entries while the other has 4000 entries. What I want to do is to see if the IP’s in the smaller dataframe appear in the IP column of the large dataframe. At the moment all I can manage is to compare the first row

Is there any method to find number of columns having data in pyspark data frame

I have a pyspark data frame that has 7 columns, I have to add a new column named “sum” and calculate a number of columns that have data (Not null) in the sum column.Example a data frame in which yellow highlighted part is required answer Answer This sum can be calculated like this: Hope this helps!

In SQL how do I group by every one of a long list of columns and get counts, assembled all into one table?

Pyspark: cast array with nested struct to string

I have pyspark dataframe with a column named Filters: “array>” I want to save my dataframe in csv file, for that i need to cast the array to string type. I tried to cast it: DF.Filters.tostring() and DF.Filters.cast(StringType()), but both solutions generate error message for each row in the columns Filters: org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@56234c19 The code is as follows Sample JSON data: