How to drop columns which have same values in all rows via pandas or spark dataframe?

What we can do is use nunique to calculate the number of unique values in each column of the dataframe, and drop the columns which only have a single unique value: In [285]: nunique = df.nunique() cols_to_drop = nunique[nunique == 1].index df.drop(cols_to_drop, axis=1) Out[285]: index id name data1 0 0 345 name1 3 1 1 … Read more

Android Studio: Duplicate files copied in APK META-INF/DEPENDENCIES when compile

While Scott Barta’s answer is correct, is lacks a simple and common solution: just add android { packagingOptions { exclude ‘META-INF/DEPENDENCIES’ exclude ‘META-INF/NOTICE’ exclude ‘META-INF/LICENSE’ exclude ‘META-INF/LICENSE.txt’ exclude ‘META-INF/NOTICE.txt’ } } to your build.gradle to ignore those duplicates.

Removing Duplicates From Dictionary

You could go though each of the items (the key value pair) in the dictionary and add them into a result dictionary if the value was not already in the result dictionary. input_raw = {112762853378: {‘dst’: [‘10.121.4.136’], ‘src’: [‘1.2.3.4’], ‘alias’: [‘www.example.com’] }, 112762853385: {‘dst’: [‘10.121.4.136’], ‘src’: [‘1.2.3.4’], ‘alias’: [‘www.example.com’] }, 112760496444: {‘dst’: [‘10.121.4.136’], ‘src’: [‘1.2.3.4’] … Read more

Removing duplicate rows (based on values from multiple columns) from SQL table

Sample SQL FIDDLE 1) Use CTE to get max ship code value record based on ARDivisionNo, CustomerNo for each Customers WITH cte AS ( SELECT*, row_number() OVER(PARTITION BY ARDivisionNo, CustomerNo ORDER BY ShipToCode desc) AS [rn] FROM t ) Select * from cte WHERE [rn] = 1 2) To Delete the record use Delete query … Read more

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