Need help writing a dataframe into a csv with the help of a loop

Question

I am trying to write a df to a csv from a loop, each line represents a df, but I am finding some difficulties once the headers are not equal for all dfs, some of them have values for all dates and others no.

I'm trying to write a data frame to csv using a loop. I'm having some difficulties doing the same once the headers of the dataframes start changing for example some of the values have dates and others dont.

I'm using a function similar to this one for writing :

[code]
def write_csv():
    for name, df in data.items():
        df.to_csv(meal+'mydf.csv', mode='a')
        [/code]

and it creates a csv for each meal (lunch an dinner) each df is similar to this:

Name    Meal    22-03-18    23-03-18    25-03-18        
Peter   Lunch   12          10          9

or:

Name    Meal    22-03-18    23-03-18    25-03-18        
Peter   Dinner  12          10          9

I have previously tried to use pandas concatenate, but I simply cant find a way to implement this in the function.
My goal is to have the headers with all the dates independent of the dataframes appended to the csv.

Actual output:
Name    Meal    22-03-18    23-03-18    25-03-18        
Peter   Lunch   12          10          9       
Mathew  Lunch   12          11          11         10     9
Ruth    Lunch   9           9           8          9    
Anna    Lunch   10          12          11         13     10

output with headers:
Name    Meal    22-03-18    23-03-18    25-03-18           
Peter   Lunch   12          10          9       
Name    Meal    21-03-18    22-03-18    23-03-18    24-03-18    25-03-18
Mathew  Lunch   12          11          11          10          9
Name    Meal    21-03-18    22-03-18    24-03-18    25-03-18    
Ruth    Lunch   9           9           8           9   
Name    Meal    21-03-18    22-03-18    23-03-18    24-03-18    25-03-18
Anna    Lunch   10          12          11          13          10

Output desired:
Name    Meal    21-03-18    22-03-18    23-03-18    24-03-18    25-03-18
Peter   Lunch   12          10          9   
Mathew  Lunch               12          11          11           10
Ruth    Lunch   9           9           8           9
Anna    Lunch   10          12          11          13           10

Answer 1

Using the following logic you can arrive at the desired output

it was necessary to create an empty df, than populate it, then groupby meal and print to csv

It is absolutely necessary that you create an empty dataframe, then populate it and then group by the meals and then print it to a csv

[code]
main_df= pd.DataFrame()

    for name, df in data.items():
        main_df = pd.concat([main_df, df])  

    main_df_group = main_df.groupby('Meal')
    for name, group in main_df_group:
        mydf_group = group

        mydf_group.to_csv(meal+ ...)
[/code]