pandas dataframe query by ndarray

Question

i have a color dataframe with 4 columns and an array of [3,]

index = ["color","R", "G", "B"] # index as csv file definition
colors_csv = read_csv(csv_path , names=index, header=None)
colors = [[159 147 134][252 252 252][ 75  81  75][229 195 184]] # sample RGB data

i want to get a new sub dataframe from colors_csv with all the occurrence of colors in R,G,B columns

by far using .loc property will return me a correct list but consist of concatenated item which i can't iterate through and acquire new dataframe

# query with array of colors 
for i in range(len(colors)):
    aaaa = ([colors_csv.loc[(colors_csv['R'] == colors[i][0]) & 
        (colors_csv['G'] == colors[i][1]) & (colors_csv['B'] == colors[i][2])]])
    print(aaaa) # how to have all these aaaa thorough loop as one dataframe

and i guess there could be a one line magic code which can do the job :)

any help appreciated

jezrael · Accepted Answer · 2021-07-30 08:38:02Z

2

Use merge with default merge by all columns with DataFrame created from RGB data:

colors_csv = read_csv(csv_path , names=index, header=None)

out = colors_csv.merge(pd.DataFrame(colors, columns=["R", "G", "B"]))

answered Jul 30, 2021 at 8:38

jezrael

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