Pandas `dropna()` by column number
In Pandas,
df.dropna(subset=['Name of the column'])
remove all the rows of the database df
according to the presence of a NaN sting in the column Name of the column
. This is very nice but it will be simpler for me to do this by the number of the colomn detected by iloc
. But I do not find the way in the documentation and in the question answer posted on the Net.
Could somebody help. Thanks
I do not know if this is an answer to my question but in fact the colomns are known by keys (number or strings). The advantage is that if adds a new column one continues to have access to any column by the key. But if the keys are too long (my cases) it becomes boring.