Python Pandas: How to move one row to the first row of a Dataframe?

Question

Given an existing Dataframe that is indexed.

>>> df = pd.DataFrame(np.random.randn(10, 5),columns=['a', 'b', 'c', 'd', 'e'])
>>> df
          a         b         c         d         e
0 -0.131666 -0.315019  0.306728 -0.642224 -0.294562
1  0.769310 -1.277065  0.735549 -0.900214 -1.826320
2 -1.561325 -0.155571  0.544697  0.275880 -0.451564
3  0.612561 -0.540457  2.390871 -2.699741  0.534807
4 -1.504476 -2.113726  0.785208 -1.037256 -0.292959
5  0.467429  1.327839 -1.666649  1.144189  0.322896
6 -0.306556  1.668364  0.036508  0.596452  0.066755
7 -1.689779  1.469891 -0.068087 -1.113231  0.382235
8  0.028250 -2.145618  0.555973 -0.473131 -0.638056
9  0.633408 -0.791857  0.933033  1.485575 -0.021429
>>> df.set_index("a")
                  b         c         d         e
a                                                
-0.131666 -0.315019  0.306728 -0.642224 -0.294562
 0.769310 -1.277065  0.735549 -0.900214 -1.826320
-1.561325 -0.155571  0.544697  0.275880 -0.451564
 0.612561 -0.540457  2.390871 -2.699741  0.534807
-1.504476 -2.113726  0.785208 -1.037256 -0.292959
 0.467429  1.327839 -1.666649  1.144189  0.322896
-0.306556  1.668364  0.036508  0.596452  0.066755
-1.689779  1.469891 -0.068087 -1.113231  0.382235
 0.028250 -2.145618  0.555973 -0.473131 -0.638056
 0.633408 -0.791857  0.933033  1.485575 -0.021429

How to move the 3rd row to the first row?

That says, expected result:

                  b         c         d         e
a                                                
-1.561325 -0.155571  0.544697  0.275880 -0.451564
-0.131666 -0.315019  0.306728 -0.642224 -0.294562
 0.769310 -1.277065  0.735549 -0.900214 -1.826320
 0.612561 -0.540457  2.390871 -2.699741  0.534807
-1.504476 -2.113726  0.785208 -1.037256 -0.292959
 0.467429  1.327839 -1.666649  1.144189  0.322896
-0.306556  1.668364  0.036508  0.596452  0.066755
-1.689779  1.469891 -0.068087 -1.113231  0.382235
 0.028250 -2.145618  0.555973 -0.473131 -0.638056
 0.633408 -0.791857  0.933033  1.485575 -0.021429

Now the original first row should become the second row.

Answer 1

To move the third row to the first, you can create an index moving the target row to the first element. I use a conditional list comprehension to join by lists.

Then, just use iloc to select the desired index rows.

np.random.seed(0)
df = pd.DataFrame(np.random.randn(5, 3),columns=['a', 'b', 'c'])
>>> df
          a         b         c
0  1.764052  0.400157  0.978738
1  2.240893  1.867558 -0.977278
2  0.950088 -0.151357 -0.103219
3  0.410599  0.144044  1.454274
4  0.761038  0.121675  0.443863

target_row = 2
# Move target row to first element of list.
idx = [target_row] + [i for i in range(len(df)) if i != target_row]

>>> df.iloc[idx]
          a         b         c
2  0.950088 -0.151357 -0.103219
0  1.764052  0.400157  0.978738
1  2.240893  1.867558 -0.977278
3  0.410599  0.144044  1.454274
4  0.761038  0.121675  0.443863

if desired, you can also reset your index.

>>> df.iloc[idx].reset_index(drop=True)
          a         b         c
0  0.950088 -0.151357 -0.103219
1  1.764052  0.400157  0.978738
2  2.240893  1.867558 -0.977278
3  0.410599  0.144044  1.454274
4  0.761038  0.121675  0.443863

Alternatively, you can just reindex the list using idx:

>>> df.reindex(idx)
          a         b         c
2  0.950088 -0.151357 -0.103219
0  1.764052  0.400157  0.978738
1  2.240893  1.867558 -0.977278
3  0.410599  0.144044  1.454274
4  0.761038  0.121675  0.443863