How to update dataframe with values from a tuple-CodePudding

I am trying to update a dataframe row based on a list of tuples. The tuple will contain a colum name (stage name) and value for stage depending on if it passed or not.

example:

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

I generated a empty data frame and populated the colum names and the stage names like so ...

df = df.append({'project_name' : current_project}, ignore_index=True)
       project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5 
0       [project 1]    NaN        NaN         NaN         NaN       NaN

However, I can't seem to update the colum correctly by extracting the tuple and using a condition to update the row. No matter what I try...

for details in stage_data:
    (item, item_status) = details
    #print(item, item_status)
    df.loc[df.project_name == current_project, item] = item_status
print(df)

the result is alway the same:

       project_name    Stage 1    Stage 2    Stage 3    Stage 4   Stage 5 
0       [project 1]    NaN        NaN         NaN         NaN       NaN

Can someone tell me what I am missing?

Thanks,

CodePudding user response：

I think here is problem is list in column project_name, so if compare get False and no update. Solution is select first value by indexing:

stage_data = [('Stage 1','SUCCESS'),('Stage 2','DELAYED')]
df = pd.DataFrame({'project_name': [['project 1'],['project 2']]})


current_project = 'project 1'
for details in stage_data:
    (item, item_status) = details
    #print(item, item_status)
    print (df.project_name == current_project)
    print (df.project_name.str[0] == current_project)
    
    0    False
    1    False
    Name: project_name, dtype: bool
    0     True
    1    False
    Name: project_name, dtype: bool


    0    False
    1    False
    Name: project_name, dtype: bool
    0     True
    1    False
    Name: project_name, dtype: bool

    df.loc[df.project_name.str[0] == current_project, item] = item_status
    
print (df)
  project_name  Stage 1  Stage 2
0  [project 1]  SUCCESS  DELAYED
1  [project 2]      NaN      NaN