Adding a row to indexed dataframe pandas

Question

I have a dataframe:

df = pd.DataFrame({'a':[1,2,3,4,5],'b':[100,200,300,400,500],'c':['a','b','j','e','q']})   
df = df.set_index(['a','b'])  #(this is sample structure, i will be having directly the indexed df)

       c
a  b     
1 100  a
2 200  b
3 300  j
4 400  e
5 500  q

This is my input multi-indexed dataframe

I have 3 variables:

a1 = 7
b1 = 700
c1 = z

(a1,b1)   c

i want to add this as a new row to the multi-indexed dataframe, without unsetting the index and then re-creating.

Final result also as a multi-indexed dataframe.

Final output required.

One way is to unset the index first, append the row, and then re-create the index.( but the actual size of my df will be around 1 million) so this might affect performance.

Is it possible to add row to multi-indexed dataframe apart from the method mentioned above?

jezrael · Accepted Answer · 2018-04-26 09:29:31Z

1

You can use if this combination does not exist in original MultiIndex:

df.loc[(a1,b1), 'c'] = c1
print (df)
       c
a b     
1 100  a
2 200  b
3 300  j
4 400  e
5 500  q
7 700  z

If combination exist original value is overwritten:

a1 = 1
b1 = 100
c1 = 'z'
df.loc[(a1,b1), 'c'] = c1
print (df)
       c
a b     
1 100  z # a to z
2 200  b
3 300  j
4 400  e
5 500  q

edited Apr 26, 2018 at 9:29

answered Apr 26, 2018 at 9:24

jezrael

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1 Comment

Shubham R Over a year ago

Didnt't think it was this simple! :)

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