I have a dict of the following form
dict = {
"Lightweight_model_20221103_downscale_1536px_RecOut": {
"CRR": "75.379",
"Sum Time": 33132,
"Sum Detection Time": 18406,
"images": {
"uk_UA_02 (1).jpg": {
"Time": "877",
"Time_detection": "469"
},
"uk_UA_02 (10).jpg": {
"Time": "914",
"Time_detection": "323"
},
"uk_UA_02 (11).jpg": {
"Time": "1169",
"Time_detection": "428"
},
"uk_UA_02 (12).jpg": {
"Time": "881",
"Time_detection": "371"
},
"uk_UA_02 (13).jpg": {
"Time": "892",
"Time_detection": "335"
}
}
},
"Lightweight_model_20221208_RecOut": {
"CRR": "71.628",
"Sum Time": 41209,
"Sum Detection Time": 25301,
"images": {
"uk_UA_02 (1).jpg": {
"Time": "916",
"Time_detection": "573"
},
"uk_UA_02 (10).jpg": {
"Time": "927",
"Time_detection": "442"
},
"uk_UA_02 (11).jpg": {
"Time": "1150",
"Time_detection": "513"
},
"uk_UA_02 (12).jpg": {
"Time": "1126",
"Time_detection": "531"
},
"uk_UA_02 (13).jpg": {
"Time": "921",
"Time_detection": "462"
}
}
}
}
and I want to make DataFrame with sub-columns in output like on image
[![enter image description here][1]][1]
but I don't understand how to open subdicts in ['images'] when I use code
df = pd.DataFrame.from_dict(dict, orient='index')
df_full = pd.concat([df.drop(['images'], axis=1), df['images'].apply(pd.Series)], axis=1)
receive dictionaries in columns whit filenames
[![result][2]][2]
how to open nested dicts and convert them to sub-columns [1]: