I'm trying to using pandas to append a blank row based on the values in the first column. When the first six characters in the first column don't match, I want an empty row between them (effectively creating groups). Here is an example of what the output could look like:

002446

002447-01
002447-02

002448

This is what I was able to put together thus far.

readie=pd.read_csv('title.csv')
i=0
for row in readie:
    readie.append(row)
    i =1
    if readie['column title'][i][0:5]!=readie['column title'][i 1][0:5]:
        readie.append([])

When running this code, I get the following error message:

TypeError: cannot concatenate object of type '<class 'str'>'; only Series and DataFrame objs are valid

I believe there are other ways to do this, but I would like to use pandas if at all possible.

CodePudding user response：

I'm using the approach from this answer.

Assuming that strings like '123456' and '123' are considered as not matching:

df_orig = pd.DataFrame(
    {'col':['002446','002447-01','002447-02','002448','00244','002448']}
)

df = df_orig.reset_index(drop=True)  # reset your index
first_6 = df['col'].str.slice(stop=6)
mask = first_6 != first_6.shift(fill_value=first_6[0])
df.index = df.index   mask.cumsum() 
df = df.reindex(range(df.index[-1]   1))

print(df)

         col
0     002446
1        NaN
2  002447-01
3  002447-02
4        NaN
5     002448
6        NaN
7      00244
8        NaN
9     002448