Reputation: 644
I have a dataframe like
address balance
0 0xa04fc9 1136151.200472032
1 0x1937c5 1000000.0
2 0xff7843 933580.0
3 0x528173 660354.97467932
4 0x6eb557 660000.0
5 0x198ef1 608334.724
6 0x1b3cb8 560000.0
7 0x51f9c4 530000.0
8 0x2b717c 500000.0
. ...
I want to add, let's say, 20 rows at the end of the data frame such that
address balance
0 0xa04fc9 1136151.200472032
1 0x1937c5 1000000.0
2 0xff7843 933580.0
3 0x528173 660354.97467932
4 0x6eb557 660000.0
5 0x198ef1 608334.724
6 0x1b3cb8 560000.0
7 0x51f9c4 530000.0
8 0x2b717c 500000.0
. 0
. 0
. 0
. 0
28 0
Any help will be appreciated!
Upvotes: 2
Views: 2284
Reputation: 191
you can also use the df.reindex()
method
say you need to add 5 new rows to you df
dataframe with 0
as value
df = df.reindex([*range(len(df)+5)],fill_value = 0)
Upvotes: 1
Reputation: 862511
Use concat
with DataFrame
constructor:
df = pd.concat([df,
pd.DataFrame(0, columns=['balance'], index=range(20))], ignore_index=True)
print (df)
address balance
0 0xa04fc9 1.136151e+06
1 0x1937c5 1.000000e+06
2 0xff7843 9.335800e+05
3 0x528173 6.603550e+05
4 0x6eb557 6.600000e+05
5 0x198ef1 6.083347e+05
6 0x1b3cb8 5.600000e+05
7 0x51f9c4 5.300000e+05
8 0x2b717c 5.000000e+05
9 NaN 0.000000e+00
10 NaN 0.000000e+00
11 NaN 0.000000e+00
12 NaN 0.000000e+00
13 NaN 0.000000e+00
14 NaN 0.000000e+00
15 NaN 0.000000e+00
16 NaN 0.000000e+00
17 NaN 0.000000e+00
18 NaN 0.000000e+00
19 NaN 0.000000e+00
20 NaN 0.000000e+00
21 NaN 0.000000e+00
22 NaN 0.000000e+00
23 NaN 0.000000e+00
24 NaN 0.000000e+00
25 NaN 0.000000e+00
26 NaN 0.000000e+00
27 NaN 0.000000e+00
28 NaN 0.000000e+00
Upvotes: 3