Python Pandas - Append data to specific row and column -

after searching, don't think duplicate, if please let me know.

i have data frame number of rows , variables. create separate data frame of single row mean of each variable. i'm doing can plot in graph. i'm not sure why syntax doesn't work.

this 1 specific variable. if can work, can expand columns loop.

avg = pd.dataframe(columns=original.columns.values) avg['max_yds'].loc[0] = original['max_yds'].mean(axis=0) 

in mind, first line creates data frame called 'avg' empty , has columns original. seems work expected. second line, expect set first row of variable 'max_yds' in 'avg' , set mean of variable of 'max_yds' original. instead, get: empty dataframe

thanks!

try

avg.set_value(0, 'max_yds', original['max_yds'].mean(axis=0)) 

if want compute mean columns, why not use

avg = avg.append(original.mean(axis=0), ignore_index=true) 

edit:

the problem of original solution using kind of "chained indexing", bad.

you add value series in each column, index of dataframe still empty.

actually, if add

avg['max_yds'] = avg['max_yds'] 

after

avg['max_yds'].loc[0] = original['max_yds'].mean(axis=0) 

, code work well.

or can specify index @ beginning, can fix problem.

avg = pd.dataframe(columns=original.columns.values, index=[0]) 

however, not recommended so.