Add values to dataframe column after certain index

Question

I have a dataframe like this:

No     Data    Sentence
32      xxx      yyyy
45      hhh      uuuu
 .       .        . 
 .       .        . 
8726    aaa      bbbb

Where the No column is unordered, now I have x which is list of sentences and I want to add that list to the Sentence column after my last index. So my new dataframe will look like:

No     Data    Sentence
32      xxx      yyyy
45      hhh      uuuu
    .       .         . 
    .       .         . 
8726    aaa      bbbb
NaN     NaN      x[0]
NaN     NaN      x[1]
 .       .         .
 .       .         .
NaN     NaN      x[n]

I know we can directly assign list to column by assign function but it'll assign list value from beginning and I don't even know size of my list. Can someone help me with this?

Shaido · Accepted Answer · 2019-05-02 06:49:08Z

1

Convert the list of sentences to a dataframe and then use pd.concat:

x = pd.DataFrame({'Sentence': x})
pd.concat([df,x], axis=0, ignore_index=True)

answered May 2, 2019 at 6:49

Shaido

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2 Comments

VIBHU BAROT Over a year ago

exactly what I was looking for. Thank you very muchh for help

Shaido Over a year ago

@VIBHUBAROT: Happy to help :)

Tabbakhh · Accepted Answer · 2019-05-02 06:53:04Z

1

First turn your list into a dataframe:

listDF = pd.DataFrame(list, columns='Sentence')

Then use pandas.DataFrame.append

extended_df = df.appned(listDF)

To test:

create df1:

df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))

print it:

   A  B
0  1  2
1  3  4

create df2:

df2 = pd.DataFrame([5, 6], columns=list('B'))

print it:

   B
0  5
1  6

finally:

df.append(df2)

results:

     A  B
0  1.0  2
1  3.0  4
0  NaN  5
1  NaN  6

answered May 2, 2019 at 6:53

Tabbakhh

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