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Let's assume I have the following data frame:

          x         y
1    -1.808909  0.093380
2     1.733595 -0.380938
3    -1.385898  0.714071

And I want to insert a value in the column after "y". However, it's possible that I might insert more than one value.

So, I need to check if the cell after "y" is empty or not to avoid overwriting the cell.

so, the expected output might be like

          x         y      
1    -1.808909  0.093380   5
2     1.733595 -0.380938   6    7
3    -1.385898  0.714071   8

Compared to the input above, I need to check the cell first if it's empty or not.

I thought I might use: x = df.iloc[1,:].last_valid_index()

but that method returns "y" not the index of "y" which is 1.

later I'll use that index to inset "5":

x +=1
df.iloc[1,x] = 5

I want to use that approach of finding the last non-empty cell because of the 2nd row in the output. You see that I need to insert "6" then "7" If I ended up using always the same method like this one:

    df.iloc[1,2] = 6
    df.iloc[1,2] = 7

It'll overwrite the "6" when inserting "7"

One more thing, I can't look for the value using something like: (df['y'].iloc[2]).index because later I'll have two "y" columns so, that might leads to returns index number less than the required.

Ahmed Nabil
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    Can you post input dataframe and expected output? – Scott Boston Sep 17 '22 at 15:48
  • @ScottBoston Done – Ahmed Nabil Sep 17 '22 at 16:07
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    Refrain from showing your dataframe as an image. Your question needs a minimal reproducible example consisting of sample input, expected output, actual output, and only the relevant code necessary to reproduce the problem. See [How to make good reproducible pandas examples](https://stackoverflow.com/questions/20109391/how-to-make-good-reproducible-pandas-examples) for best practices related to Pandas questions. – itprorh66 Sep 17 '22 at 16:11
  • I simplified the question – Ahmed Nabil Sep 17 '22 at 18:06

2 Answers2

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It is easy to identify the position of the first zero in each row in a numpy array or a dataframe. Let's create a dataframe with zeros after a certain position:

df = pd.DataFrame(np.random.normal(size=(5, 10)))
df

   0  1  2  3  4  5  6  7  8  9
0  4  1  4  2  6  0  0  0  0  0
1  5  4  9  5  5  4  0  0  0  0
2  6  6  6  5  4  8  6  0  0  0
3  5  3  9  5  3  9  6  3  0  0
4  3  2  7  9  7  6  6  7  5  0

For instance, the code below will give you all positions in the dataframe where the value is 0

np.argwhere(df.values == 0)

array([[0, 5],
       [0, 6],
       [0, 7],
       [0, 8],
       [0, 9],
       [1, 6],
       [1, 7],
       [1, 8],
       [1, 9],
       [2, 7],
       [2, 8],
       [2, 9],
       [3, 8],
       [3, 9],
       [4, 9]], dtype=int64)

Or you can get the positions where the values are not zero:

np.argwhere(df.values != 0)

array([[0, 0],
       [0, 1],
       [0, 2],
       [0, 3],
       [0, 4],
       [1, 0],
       [1, 1],
       [1, 2],
       [1, 3],
       [1, 4],
       [1, 5],
       [2, 0],
       [2, 1],
       [2, 2],
       [2, 3],
       [2, 4],
       [2, 5],
       [2, 6],
       [3, 0],
       [3, 1],
       [3, 2],
       [3, 3],
       [3, 4],
       [3, 5],
       [3, 6],
       [3, 7],
       [4, 0],
       [4, 1],
       [4, 2],
       [4, 3],
       [4, 4],
       [4, 5],
       [4, 6],
       [4, 7],
       [4, 8]], dtype=int64)

I hope it helps.

vtec
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  • Thank you for your help, I modified the question a little bit because I think I didn't elaborate enough at the first time I still don't know how to use it in my case to check the last non-empty values :) – Ahmed Nabil Sep 17 '22 at 18:22
  • Still not 100% sure about what your final result should be but here are two hints: Can you just add in the question above what you input and what you output should be? df in and df out. Otherwise it is not easy to really help you. – vtec Sep 25 '22 at 11:37
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I suggest this, a less complicated solution

import random
nums = [0, 7, 78, 843, 34893, 0 , 2, 23, 4, 0]
random.shuffle(nums)
thg = [x for x in nums if x != 0]
print(thg[0])

what this does is shuffle the 'nums' list and filters out all the zeros. Then it prints the first non-zero value

anonymous
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