Count number of characters in each row and drop if all are below a certain number
I have a dataframe with many columns, all of which contain text data mixed with NaNs.
Count number of characters in each row and drop if all are below a certain number
I have a dataframe with many columns, all of which contain text data mixed with NaNs.
Convert range of numbers to average in a pandas dataframe cell
I have a pandas dataframe read from large spreadsheets provided through a survey. In a column that expects float input, some of the cell entries are expressed as “n1-n2” (where n1 and n2 are numbers). I need to go through such columns and convert each such instance to (n1+n2)/2. Can someone suggest a lambda apply function for this to do this in the most pythonic way?
Convert range of numbers to average in a pandas dataframe
I have a pandas dataframe read from large spreadsheets provided through a survey. In a column that expects float input, some of the cell entries are expressed as “n1-n2” (where n1 and n2 are numbers). I need to go through such columns and convert each such instance to (n1+n2)/2. Can someone suggest a lambda apply function for this to do this in the most pythonic way?
Extract the string from one column when matches with another string list to make a new column
I have a dataframe: