Pandas adding a row into a DataFrame

Question

I am writing a little function that would incrementaly add rows into a DataFrame using pandas. The core goes like this:

DB =  pd.DataFrame(columns=['MAN','MOD','YEAR','TYPE']) 
for id, row is other_dataFrame.iterrows():
    DB = pd.concat([self.loadedDB, row.to_frame().T])

using print, I get that initial DB looks like this:

Empty DataFrame
Columns: [MAN, MOD, YEAR, TYPE]
Index: []

while row may look like this:

MAN      Aixam
 MOD       400
 YEAR     1930
 TYPE      NaN
Name: 0, dtype: object

then, after the loop the resulting DB looks like this:

           MAN  MOD YEAR TYPE             MOD  YEAR  TYPE
0        Aixam  NaN  NaN  NaN             400  1930   NaN
1          BMW  NaN  NaN  NaN              I3  1930   NaN
2      Bollore  NaN  NaN  NaN         Bluecar  1930   NaN
3          BYD  NaN  NaN  NaN              e6  1930   NaN
4        Buddy  NaN  NaN  NaN             Cab  1930   NaN
5        Chery  NaN  NaN  NaN             QQ3  1930   NaN
6    Chevrolet  NaN  NaN  NaN        Spark EV  1930   NaN
7      Dynasty  NaN  NaN  NaN              IT  1930   NaN
8         Ford  NaN  NaN  NaN  Focus Electric  1930   NaN
...

while I would, of course, like to have it in format of:

           MAN  MOD  YEAR  TYPE
0        Aixam  400  1930   NaN
1          BMW  I3  1930   NaN
2      Bollore  Bluecar  1930   NaN
3          BYD  e6  1930   NaN
4        Buddy  Cab  1930   NaN
5        Chery  QQ3  1930   NaN
6    Chevrolet  Spark EV  1930   NaN
7      Dynasty  IT  1930   NaN
8         Ford  Focus Electric  1930   NaN
...

Can anyone please tell me what am I doing wrong? This is the first time I use pandas, so it is possible that the answer is really simple, however I cant find it. Thank you

It appears that you're combining two dataframes, Why add one row at a time, instead of putting them together in a single step? — BeRT2me
– BeRT2me, Commented Sep 28, 2022 at 21:59
In further step the adding will be conditioned, so I cannot do that at once — Adam
– Adam, Commented Sep 28, 2022 at 22:00
well i may want to check whether the MAN and MOD attrs of the poentional new row arent already with in the DS. In that case, I would not add the new row, even if YEAR and TYPE attrs would be different — Adam
– Adam, Commented Sep 28, 2022 at 22:05
Sounds like a simple merge operation. Does this answer your question? Pandas Merging 101 — BeRT2me
– BeRT2me, Commented Sep 28, 2022 at 22:06

datasor · Accepted Answer · 2022-09-28 22:13:25Z

2

This should work:

DB =  pd.DataFrame(columns=['MAN','MOD','YEAR','TYPE']) 
for id, row in other_dataFrame.iterrows():
    DB.loc[len(DB)] = [row['MAN'], row['MOD'], row['YEAR'], row['TYPE']]

Just appending a list to the empty dataframe at its last position. There may be an easier way to convert the row object to list, couldn't find it.

answered Sep 28, 2022 at 22:13

datasor

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Comments

Xnot · Accepted Answer · 2022-09-28 23:01:44Z

1

Your original code should work. You should try printing self.loadedDB.columns and row.to_frame().T.columns to verify if there's any whitespace in these column names, causing them to be concatenated as separate columns.

answered Sep 28, 2022 at 23:01

Xnot

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