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.
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
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