I have a dataframe like as shown below What I would like to do is copy non-na rows from Test column and paste it in corresponding row under sourcename column When I tried the below, it makes the other rows of sourcename column as NA I expect my output to be like as shown below Answer One idea with Series.fillna:
Tag: na
How to cycle the NaNs in pandas dataframe rows?
I have a dataframe like this: How to put all the NAs in the left instead of right? Required: Answer There are mixed numeric with strings rows, so solution is use sorted with key parameter in DataFrame.apply: If all values are numeric, faster solution is with justify:
How do you represent missing data in a Pandas DataFrame?
Does Pandas have an equivalent of R’s na (meaning not available)? If not, what is the convention for representing a missing value, as opposed to NaN which represents a mathematically impossible value such as a divide by zero? Answer Currently there is no NA value available in Pandas or NumPy. From the section “Working with missing data” in the Pandas