Python：将所有实例从循环中保存到变量中，以便以后调用

Question

I'm working with Pandas and a CSV file that I'm iterating through in order to find every occurrence of a specific color and then returning the image's name. For example, I have a dataframe:

    imageName   color1   color2   color3   color4  
    1           Blue     Blue     Blue     Blue 
    2           Pink     Magenta  Red      Purple
    3           Blue     Blue     Blue     Blue
    4           Blue     Yellow   Teal     Teal
    5           Yellow   Blue     Red      Purple
    ...

What I'm doing is printing the image name each time a specific color is mentioned.

   for index, row in df.iterrows():
      if (row['color1'] == 'Blue' and row['color2'] == 'Blue' and row['color3'] == 'Blue' and row['color4'] == 'Blue'):
         allBlue = (row['imageName'])

This gets me the results that I want, but if I call my variable allBlue from a different file, it just returns the last instance since it's not in a for loop. Is there a way to save the whole print out to a variable to call later from a different file?

Like this: When I call it from inside loop

Occurrences of all Blue Shapes:
1
3
6
19
...
178

Instead of this: When I call it from other file

Occurrences of all Blue Shapes:
178

I'm fairly certain I'm just forgetting something obvious or not thinking about something clearly, but any help would be much appreciated.

Answer 1

You don't need the loop to find images-with-a-color in pandas. However, I put in a loop that uses the accumulator-list in the right place as an example ( colorcols ):

import pandas as pd

cdf = pd.DataFrame({'color1': {0: 'Red', 1: 'Blue', 2: 'Yellow', 3: 'Blue'},
 'color2': {0: 'Red', 1: 'Green', 2: 'Blue', 3: 'Blue'},
 'color3': {0: 'Red', 1: 'Red', 2: 'Red', 3: 'Blue'},
 'color4': {0: 'Red', 1: 'Blue', 2: 'White', 3: 'Blue'},
 'form': {0: 'circle', 1: 'circle', 2: ' square', 3: 'circle'},
 'imageName': {0: 'img1', 1: 'img2', 2: 'img3', 3: 'img4'}})

colorcols = []
for i in range(1,5):
    colorcols.append('color%d'%i)

for color in set(cdf[colorcols].values.flatten()):
    mask = (cdf==color)
    print('%s: '%color),
    colors = (mask.sum(axis=1) > 0)

    print(cdf[colors].imageName.values)

 Blue: ['img2' 'img3' 'img4'] White: ['img3'] Green: ['img2'] Yellow: ['img3'] Red: ['img1' 'img2' 'img3']