I have a large dataset ~1mln rows, and about 5000 absent coordinates(i’d like to fill them with median value by category ‘city’everything but fillna is working, how to make it happen? Answer You could do: First groupby with the city, then use transform with fillna and calculate the median. (you could use any mathematical operation)
Tag: fillna
Faster alternative to groupby, unstack then fillna
I’m currently doing the following operations based on a dataframe (A) made of two columns with multiple thousands of unique values each. The operations performed on this dataframe are: The output is a table (B) with unique values of col1 in rows and unique values of col2 in columns, and each cell is the count of rows, from the original
How do I use python reduce function to fill NaN values
I have a dataframe with missing data in several columns. In some of these columns, say ‘Col_A’ to ‘Col_D’, I’d like to replace them with 0. I tried it this way: but I got the error message <lambda>() takes 1 positional argument but 2 were given. Eventually, I changed my solution to simply but I still wonder what’s wrong with
Python Pandas replace NaN in one column with value from corresponding row of second column
I am working with this Pandas DataFrame in Python. I need to replace all NaNs in the Temp_Rating column with the value from the Farheit column. This is what I need: If I do a Boolean selection, I can pick out only one of these columns at a time. The problem is if I then try to join them, I