CODEWITHSUNDEEP
pythonpython-3.xpandasdataframe
Azee.
Azee.

Reputation: 723

Select and concatenate DataFrame rows based on list of tuples

I have two DataFrames like this:

df_cells = pd.DataFrame({
    'left': [1095, 257],
    'top': [1247, 1148],
    'right': [1158, 616],
    'bottom': [1273, 1176] 
})

df_text = pd.DataFrame({
    'words': ['Hello', 'world', 'nice day', 'have a'],
    'left': [1097, 1099, 258, 259],
    'top': [1248, 1249, 1156, 1153],
    'right': [1154, 1156, 615, 614],
    'bottom': [1269, 1271, 1175, 1172] 
})

df_cells contains coordinates of bounding boxes for phrases on an image and df_text contains words and their bounding box coordinates on an image.

I have created a list of tuples where the bounding boxes for phrases and words match based on left, top, right, bottom values like this:

overlap = [(0,0), (1,0), (2, 1), (3, 1)]

where the first element of a tuple is the index value of df_text and the second element is matching index value of df_cells.

I want to select,combine rows based on overlap into a new dataframe like this:

Words                df_cells.left    df_cells.top    df_cells.right   df_cells.bottom
Hello                1095             1247            1158             1273
world                1095             1247            1158             1273
Have a               257              1148            616              1176
nice day             257              1148            616              1176

and afterwards concatenate words with the same left, top, right , bottom like this:

Words                df_cells.left    df_cells.top    df_cells.right   df_cells.bottom
Hello world          1095             1247            1158             1273
Have a nice day      257              1148            616              1176

Would appreciate some help with this.

Upvotes: 1

Views: 157

Answers (1)

Henry Yik
Henry Yik

Reputation: 22503

I think you can assign the values directly to df_text with index created by list comprehension:

df_text.iloc[[i[0] for i in overlap], 1:] = df_cells.iloc[[i[1] for i in overlap]].to_numpy()

print (df_text)

      words  left   top  right  bottom
0     Hello  1095  1247   1158    1273
1     world  1095  1247   1158    1273
2  nice day   257  1148    616    1176
3    have a   257  1148    616    1176

print (df_text.groupby(["left", "top", "right", "bottom"], as_index=False).agg({"words":" ".join}))

   left   top  right  bottom            words
0   257  1148    616    1176  nice day have a
1  1095  1247   1158    1273      Hello world

Upvotes: 1

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