Every row after a certain value-CodePudding

Here is part of my data:

I want to create a dataframe with every row after the row with L = ball_snap in it. So not only that specific row but every row after it as well.

How would I do that in pandas?

CodePudding user response：

You can use idxmax to return the row with L = ball_snap and use the slice notation to extract all rows after:

df1 = df.loc[df['L'].eq('ball_snap').idxmax():]

Input:

>>> df
   A  B  C          L
0  8  6  9           
1  3  1  6           
2  4  9  9           
3  1  5  1  ball_snap
4  3  7  0           
5  9  2  0           
6  1  8  4           
7  7  9  8           
8  5  9  1           
9  4  3  4

Output:

>>> df1
   A  B  C          L
3  1  5  1  ball_snap
4  3  7  0           
5  9  2  0           
6  1  8  4           
7  7  9  8           
8  5  9  1           
9  4  3  4

Update: if you don't want the row with 'ball_snap' use shift before idxmax:

df2 = df.loc[df['L'].eq('ball_snap').shift(fill_value=False).idxmax():]

Output:

CodePudding user response：

To select every row after a given index and/or including that index, you can use a Dataframe's tail method with a negative value, for example:

idx_first_ball_snap = df.index[df['L'] == 'ball_snap'].tolist()[0]
print(df.tail(-idx_first_ball_snap))

This selects the first row with "ball_snap" and also every row afterwards:

        K          L
2   47.40  ball_snap
3   46.71           
4  341.60           
5  246.74 
.
.
.
etc

Here's the documentation on DataFrame method tail: https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.tail.html

CodePudding user response：

Here is another way using cummax()

df.loc[df['L'].eq('ball_snap').cummax()]

Output:

   A  B  C          L
3  1  5  1  ball_snap
4  3  7  0        NaN
5  9  2  0        NaN
6  1  8  4        NaN
7  7  9  8        NaN
8  5  9  1        NaN
9  4  3  4        NaN