How does one combine a dataframe of different sizes....?

Question

I am trying to combine a list of projects into a master dataframe and I can't seem to figure out how to merge them together? The frame I generated are of different sizes, but most of the colum names will be the same, with the exception of one or two....

So basically, I am taking a list of project stages like so... (Some of the projects will only have 2 or 3 stages, where others will have 8 or 9 stages..) example:

Stage 1 SUCCESS
stage 2 SUCCESS
stage 3 SUCCESS
stage 4 DELAYED
stage 5 PENDING

and, I generate a dataframe like that below in a python loop...

df

       project_name    Stage 1    Stage 2     
0      project 1       SUCCESS    DELAYED

df

       project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5 
0      project-2       NaN        NaN        NaN        NaN       NaN

df

       project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5   Stage 6    Stage 7   Stage 8
0      project-3       NaN        NaN        STARTED    ABANDONED NaN       NaN        NaN       
    NaN 

However, I can't seem to figure out how to generate a master dataframe containing all the other frames...

# items passed in from other function...
project_data = [('Stage 1','SUCCESS'),('Stage 2','DELAYED')]
project_name = 'project-x' 
project_headers = ['Stage 1','Stage 2','Stage 3','Stage 4','Stage 5','Stage 6']
project_displayname = ''

# Create the pandas DataFrame
try:
    df
except NameError:
    print("Well, 'df' WASN'T defined after all!")
    df = pd.DataFrame( columns = project_headers, index=['0'])
else:
    df = df.reindex(list(range(0, 1))).reset_index(drop=True)
    df['project_name'] = project_name
    df.loc[df.project_name == project_name, "project"] = project_displayname


combined_frame = pd.DataFrame(columns = ['project_name']) # empty frame with one colum for merge
for details in project_data:
    (item, item_status) = details
    if item not in df:
        df[item] = np.nan
    df.loc[df.project_name == project_name, item] = item_status
    print('')
    print('')
    print(df)  
    print('')

# Which gives us a generated dataframe.... like so... 
#project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5   Stage 6    Stage 7   Stage 8
#project-3       NaN        NaN        STARTED    ABANDONED NaN       NaN        NaN       NaN

    #final_frame = combined_frame.merge(df, how='left')
    try:
        final_frame = pd.merge(df, combined_frame, how='outer', left_index=True, right_on=combined_frame.iloc[: , -1])
    except IndexError:
        final_frame = df.reindex_axis(df.columns.union(combined_frame.columns), axis=1)

print(final_frame)

When I run the code I get the error: Empty DataFrame

Or, I get...

Columns: [project, project_name, Stage 1, Stage 2, Stage 3, Stage 4, Stage 5, Stage 6, Stage 7, Stage 8, Stage 9]
Index: []

Or I get...

Columns: [project, project_name, Stage 1, Stage 2, Stage 3, Stage 4, Stage 5, Stage 6, Stage 7, Stage 8, Stage 9, project_x, project_name_x, Stage 1_x, Stage 2_x, Stage 3_x, Stage 4_x]
Index: []

Can someone point out the erros in my ways? Clearly I am missing something?

I would like to try and get an output like this:

   project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5   Stage 6    Stage 7   Stage 8
0  project-1       STARTED    NaN        NaN        NaN       NaN       NaN        NaN       NaN
1  project-2       STARTED    STARTED    STARTED    DELAYED   NaN       NaN        NaN       NaN
2  project-3       NaN        NaN        STARTED    ABANDONED NaN       NaN        NaN       NaN
3  project-4       NaN        NaN        STARTED    ABANDONED NaN       STARTED    NaN       NaN
4  project-5       CANCELED   NaN        NaN        NaN       NaN       NaN        NaN       NaN
5  project-6       DELAYED    DELAYED    STARTED    ABANDONED NaN       NaN        STARTED    NaN 

Thanks in advance,

E