Copy above row values below

Question

Probably easy, but couldn't find it.

Want to copy large chunk of data in row where concat data wasn't properly filled in so NaN is below values.

Small example:

df1 = {'col1': ['a', 'b','c','d','e','f','g',np.nan,np.nan,np.nan,np.nan,np.nan,np.nan,np.nan]}
df1 = pd.DataFrame(data=df1)

Did this:

df1['col1'][7:14] = df1['col1'][0:7]

Worked fine.

But what about larger data sets where I don't know the index slicing? Is there a built-in function for this?

Answer 1

Try 1) not to chain index, 2) passing numpy array on assignment:

df.loc[7:14, 'col1'] = df.loc[:7,'col1'].values

Output:

   col1
0     a
1     b
2     c
3     d
4     e
5     f
6     g
7     a
8     b
9     c
10    d
11    e
12    f
13    g