Tabulate incoming table information in json format as dataframe - python

Output from my table.py file is as follows. My goal is to create a table in dataframe format using the information from here. (I caught the values of the tables in different formats in the pdf file). values contain information corresponding to rows or columns. The other alignment information is the information returned from the csv about their location in the pdf file.now i need to tabulate them in dataframe but i couldn't find an easy way. I need your help.
{"returnData": [{"value": "Art.", "left": 123, "top": 445, "width": 16, "height": 14, "pageNo": 1,"prob": 0.8870015740394592},{"value": "Nr.", "left": 143, "top": 445, "width": 12, "height": 14, "pageNo": 1, "prob": 0.8796614408493042}, {"value": "Beschreibung", "left": 197, "top": 446, "width": 72, "height": 14, "pageNo": 1, "prob": 0.9776557683944702}, {"value": "Kolli", "left": 501, "top": 448, "width": 25, "height": 14, "pageNo": 1, "prob": 0.8893064260482788}, {"value": "Inhalt", "left": 531, "top": 448, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9761049747467041}, {"value": "Menge", "left": 593, "top": 449, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9946377873420715},{"value": "Preis", "left": 665, "top": 449, "width": 20, "height": 14, "pageNo": 1, "prob": 0.974210262298584},{"value": "€", "left": 689, "top": 449, "width": 4, "height": 14, "pageNo": 1, "prob": 0.9806452393531799},
{"value": "Betrag", "left": 743, "top": 450, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9663920998573303},{"value": "€", "left": 778, "top": 450, "width": 5, "height": 14, "pageNo": 1, "prob": 0.9893004298210144},...]}


This should be easy enough with json_normalize.
When json_string is the string you mentioned, try:
import pandas as pd
json_string = {
"returnData":[
{"value": "Art.", "left": 123, "top": 445, "width": 16, "height": 14, "pageNo": 1,"prob": 0.8870015740394592},
{"value": "Nr.", "left": 143, "top": 445, "width": 12, "height": 14, "pageNo": 1, "prob": 0.8796614408493042},
{"value": "Beschreibung", "left": 197, "top": 446, "width": 72, "height": 14, "pageNo": 1, "prob": 0.9776557683944702},
{"value": "Kolli", "left": 501, "top": 448, "width": 25, "height": 14, "pageNo": 1, "prob": 0.8893064260482788},
{"value": "Inhalt", "left": 531, "top": 448, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9761049747467041},
{"value": "Menge", "left": 593, "top": 449, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9946377873420715},
{"value": "Preis", "left": 665, "top": 449, "width": 20, "height": 14, "pageNo": 1, "prob": 0.974210262298584},
{"value": "€", "left": 689, "top": 449, "width": 4, "height": 14, "pageNo": 1, "prob": 0.9806452393531799},
{"value": "Betrag", "left": 743, "top": 450, "width": 30, "height": 14, "pageNo": 1, "prob": 0.9663920998573303},
{"value": "€", "left": 778, "top": 450, "width": 5, "height": 14, "pageNo": 1, "prob": 0.9893004298210144}
]
}
pd.json_normalize(json_string['returnData'])
returns:
value left top width height pageNo prob
Art. 123 445 16 14 1 0.887002
Nr. 143 445 12 14 1 0.879661
Beschreibung 197 446 72 14 1 0.977656
Kolli 501 448 25 14 1 0.889306
Inhalt 531 448 30 14 1 0.976105
Menge 593 449 30 14 1 0.994638
Preis 665 449 20 14 1 0.974210
€ 689 449 4 14 1 0.980645
Betrag 743 450 30 14 1 0.966392
€ 778 450 5 14 1 0.989300
Since these are column values, you can determine the left-rightbound of a column. f.e. all Art. Nr. values will be between ±123 and ±197, Beschreibung between ±197 and ±501. So you can map the following data according to that logic.

Related

How to change numbers in jsonl file and save it

I have a jsonl file with content
How to read a file and change the number after the label sign to a random number 0 or 1 and save the converted file back in python
{"idx": 0, "passage": {"questions": [{"idx": 0, "answers": [{"idx": 0, "label": 0}, {"idx": 1, "label": 0}, {"idx": 2, "label": 0}, {"idx": 3, "label": 0}]}, {"idx": 1, "answers": [{"idx": 4, "label": 0}, {"idx": 5, "label": 0}, {"idx": 6, "label": 0}, {"idx": 7, "label": 0}]}, {"idx": 2, "answers": [{"idx": 8, "label": 1}, {"idx": 9, "label": 0}, {"idx": 10, "label": 0}, {"idx": 11, "label": 0}]}, {"idx": 3, "answers": [{"idx": 12, "label": 0}, {"idx": 13, "label": 0}, {"idx": 14, "label": 0}, {"idx": 15, "label": 0}]}, {"idx": 4, "answers": [{"idx": 16, "label": 0}, {"idx": 17, "label": 0}, {"idx": 18, "label": 0}, {"idx": 19, "label": 0}, {"idx": 20, "label": 0}]}, {"idx": 5, "answers": [{"idx": 21, "label": 0}, {"idx": 22, "label": 0}, {"idx": 23, "label": 0}, {"idx": 24, "label": 0}, {"idx": 25, "label": 0}]}, {"idx": 6, "answers": [{"idx": 26, "label": 0}, {"idx": 27, "label": 0}, {"idx": 28, "label": 0}, {"idx": 29, "label": 0}, {"idx": 30, "label": 0}]}, {"idx": 7, "answers": [{"idx": 31, "label": 0}, {"idx": 32, "label": 0}, {"idx": 33, "label": 0}, {"idx": 34, "label": 0}, {"idx": 35, "label": 0}]}, {"idx": 8, "answers": [{"idx": 36, "label": 0}, {"idx": 37, "label": 0}, {"idx": 38, "label": 0}, {"idx": 39, "label": 0}, {"idx": 40, "label": 0}]}, {"idx": 9, "answers": [{"idx": 41, "label": 0}, {"idx": 42, "label": 0}, {"idx": 43, "label": 0}, {"idx": 44, "label": 0}, {"idx": 45, "label": 0}]}]}}
{"idx": 1, "passage": {"questions": [{"idx": 10, "answers": [{"idx": 46, "label": 0}, {"idx": 47, "label": 0}, {"idx": 48, "label": 0}, {"idx": 49, "label": 0}, {"idx": 50, "label": 0}]}, {"idx": 11, "answers": [{"idx": 51, "label": 0}, {"idx": 52, "label": 0}, {"idx": 53, "label": 0}, {"idx": 54, "label": 0}, {"idx": 55, "label": 0}]}]}}
{"idx": 2, "passage": {"questions": [{"idx": 12, "answers": [{"idx": 56, "label": 0}, {"idx": 57, "label": 0}, {"idx": 58, "label": 0}, {"idx": 59, "label": 0}, {"idx": 60, "label": 0}]}, {"idx": 13, "answers": [{"idx": 61, "label": 0}, {"idx": 62, "label": 0}, {"idx": 63, "label": 0}, {"idx": 64, "label": 0}, {"idx": 65, "label": 0}]}, {"idx": 14, "answers": [{"idx": 66, "label": 0}, {"idx": 67, "label": 0}, {"idx": 68, "label": 0}, {"idx": 69, "label": 0}, {"idx": 70, "label": 0}]}, {"idx": 15, "answers": [{"idx": 71, "label": 0}, {"idx": 72, "label": 0}, {"idx": 73, "label": 0}, {"idx": 74, "label": 0}, {"idx": 75, "label": 0}]}, {"idx": 16, "answers": [{"idx": 76, "label": 0}, {"idx": 77, "label": 0}, {"idx": 78, "label": 0}, {"idx": 79, "label": 0}, {"idx": 80, "label": 0}]}, {"idx": 17, "answers": [{"idx": 81, "label": 0}, {"idx": 82, "label": 0}, {"idx": 83, "label": 0}, {"idx": 84, "label": 0}, {"idx": 85, "label": 0}]}, {"idx": 18, "answers": [{"idx": 86, "label": 0}, {"idx": 87, "label": 0}, {"idx": 88, "label": 0}, {"idx": 89, "label": 0}, {"idx": 90, "label": 0}]}, {"idx": 19, "answers": [{"idx": 91, "label": 0}, {"idx": 92, "label": 0}, {"idx": 93, "label": 0}, {"idx": 94, "label": 0}, {"idx": 95, "label": 0}]}]}}
{"idx": 3, "passage": {"questions": [{"idx": 20, "answers": [{"idx": 96, "label": 0}, {"idx": 97, "label": 0}, {"idx": 98, "label": 0}, {"idx": 99, "label": 0}]}, {"idx": 21, "answers": [{"idx": 100, "label": 0}, {"idx": 101, "label": 0}, {"idx": 102, "label": 0}, {"idx": 103, "label": 0}]}, {"idx": 22, "answers": [{"idx": 104, "label": 0}, {"idx": 105, "label": 0}, {"idx": 106, "label": 0}, {"idx": 107, "label": 0}]}, {"idx": 23, "answers": [{"idx": 108, "label": 0}, {"idx": 109, "label": 0}, {"idx": 110, "label": 0}, {"idx": 111, "label": 0}]}, {"idx": 24, "answers": [{"idx": 112, "label": 0}, {"idx": 113, "label": 0}, {"idx": 114, "label": 0}, {"idx": 115, "label": 0}]}, {"idx": 25, "answers": [{"idx": 116, "label": 0}, {"idx": 117, "label": 0}, {"idx": 118, "label": 0}, {"idx": 119, "label": 0}]}, {"idx": 26, "answers": [{"idx": 120, "label": 0}, {"idx": 121, "label": 0}, {"idx": 122, "label": 0}, {"idx": 123, "label": 0}]}, {"idx": 27, "answers": [{"idx": 124, "label": 0}, {"idx": 125, "label": 0}, {"idx": 126, "label": 0}, {"idx": 127, "label": 0}]}]}}
{"idx": 4, "passage": {"questions": [{"idx": 28, "answers": [{"idx": 128, "label": 1}, {"idx": 129, "label": 1}, {"idx": 130, "label": 1}, {"idx": 131, "label": 1}, {"idx": 132, "label": 1}]}, {"idx": 29, "answers": [{"idx": 133, "label": 0}, {"idx": 134, "label": 1}, {"idx": 135, "label": 1}, {"idx": 136, "label": 0}, {"idx": 137, "label": 1}]}, {"idx": 30, "answers": [{"idx": 138, "label": 0}, {"idx": 139, "label": 0}, {"idx": 140, "label": 1}, {"idx": 141, "label": 0}, {"idx": 142, "label": 0}]}, {"idx": 31, "answers": [{"idx": 143, "label": 0}, {"idx": 144, "label": 0}, {"idx": 145, "label": 0}, {"idx": 146, "label": 0}, {"idx": 147, "label": 0}]}, {"idx": 32, "answers": [{"idx": 148, "label": 0}, {"idx": 149, "label": 0}, {"idx": 150, "label": 0}, {"idx": 151, "label": 0}, {"idx": 152, "label": 0}]}, {"idx": 33, "answers": [{"idx": 153, "label": 0}, {"idx": 154, "label": 1}, {"idx": 155, "label": 1}, {"idx": 156, "label": 1}, {"idx": 157, "label": 1}]}, {"idx": 34, "answers": [{"idx": 158, "label": 0}, {"idx": 159, "label": 0}, {"idx": 160, "label": 0}, {"idx": 161, "label": 0}, {"idx": 162, "label": 0}]}, {"idx": 35, "answers": [{"idx": 163, "label": 0}, {"idx": 164, "label": 1}, {"idx": 165, "label": 1}, {"idx": 166, "label": 0}, {"idx": 167, "label": 0}]}, {"idx": 36, "answers": [{"idx": 168, "label": 0}, {"idx": 169, "label": 0}, {"idx": 170, "label": 1}, {"idx": 171, "label": 0}, {"idx": 172, "label": 0}]}, {"idx": 37, "answers": [{"idx": 173, "label": 1}, {"idx": 174, "label": 0}, {"idx": 175, "label": 0}, {"idx": 176, "label": 0}, {"idx": 177, "label": 0}]}, {"idx": 38, "answers": [{"idx": 178, "label": 0}, {"idx": 179, "label": 1}, {"idx": 180, "label": 1}, {"idx": 181, "label": 0}, {"idx": 182, "label": 1}]}, {"idx": 39, "answers": [{"idx": 183, "label": 1}, {"idx": 184, "label": 1}, {"idx": 185, "label": 1}, {"idx": 186, "label": 0}, {"idx": 187, "label": 0}]}, {"idx": 40, "answers": [{"idx": 188, "label": 0}, {"idx": 189, "label": 0}, {"idx": 190, "label": 1}, {"idx": 191, "label": 0}, {"idx": 192, "label": 0}]}, {"idx": 41, "answers": [{"idx": 193, "label": 0}, {"idx": 194, "label": 0}, {"idx": 195, "label": 0}, {"idx": 196, "label": 0}, {"idx": 197, "label": 0}]}]}}
{"idx": 5, "passage": {"questions": [{"idx": 42, "answers": [{"idx": 198, "label": 0}, {"idx": 199, "label": 0}]}, {"idx": 43, "answers": [{"idx": 200, "label": 1}, {"idx": 201, "label": 0}]}, {"idx": 44, "answers": [{"idx": 202, "label": 0}, {"idx": 203, "label": 0}, {"idx": 204, "label": 0}, {"idx": 205, "label": 0}]}, {"idx": 45, "answers": [{"idx": 206, "label": 0}, {"idx": 207, "label": 0}, {"idx": 208, "label": 0}, {"idx": 209, "label": 0}]}, {"idx": 46, "answers": [{"idx": 210, "label": 0}, {"idx": 211, "label": 0}, {"idx": 212, "label": 0}, {"idx": 213, "label": 0}]}, {"idx": 47, "answers": [{"idx": 214, "label": 0}, {"idx": 215, "label": 0}, {"idx": 216, "label": 0}, {"idx": 217, "label": 0}]}, {"idx": 48, "answers": [{"idx": 218, "label": 0}, {"idx": 219, "label": 0}, {"idx": 220, "label": 0}, {"idx": 221, "label": 0}, {"idx": 222, "label": 0}]}, {"idx": 49, "answers": [{"idx": 223, "label": 1}, {"idx": 224, "label": 0}, {"idx": 225, "label": 0}, {"idx": 226, "label": 0}, {"idx": 227, "label": 0}]}, {"idx": 50, "answers": [{"idx": 228, "label": 1}, {"idx": 229, "label": 0}, {"idx": 230, "label": 0}, {"idx": 231, "label": 0}, {"idx": 232, "label": 0}]}, {"idx": 51, "answers": [{"idx": 233, "label": 0}, {"idx": 234, "label": 0}, {"idx": 235, "label": 0}, {"idx": 236, "label": 0}, {"idx": 237, "label": 0}]}, {"idx": 52, "answers": [{"idx": 238, "label": 1}, {"idx": 239, "label": 0}, {"idx": 240, "label": 0}, {"idx": 241, "label": 0}, {"idx": 242, "label": 0}]}, {"idx": 53, "answers": [{"idx": 243, "label": 0}, {"idx": 244, "label": 0}, {"idx": 245, "label": 0}, {"idx": 246, "label": 1}, {"idx": 247, "label": 1}]}, {"idx": 54, "answers": [{"idx": 248, "label": 1}, {"idx": 249, "label": 1}, {"idx": 250, "label": 1}, {"idx": 251, "label": 1}, {"idx": 252, "label": 0}]}, {"idx": 55, "answers": [{"idx": 253, "label": 0}, {"idx": 254, "label": 0}, {"idx": 255, "label": 0}, {"idx": 256, "label": 0}, {"idx": 257, "label": 0}]}]}}
{"idx": 6, "passage": {"questions": [{"idx": 56, "answers": [{"idx": 258, "label": 1}, {"idx": 259, "label": 0}, {"idx": 260, "label": 1}, {"idx": 261, "label": 0}]}, {"idx": 57, "answers": [{"idx": 262, "label": 1}, {"idx": 263, "label": 1}, {"idx": 264, "label": 1}]}, {"idx": 58, "answers": [{"idx": 265, "label": 1}, {"idx": 266, "label": 1}, {"idx": 267, "label": 1}, {"idx": 268, "label": 1}]}, {"idx": 59, "answers": [{"idx": 269, "label": 1}, {"idx": 270, "label": 1}, {"idx": 271, "label": 1}, {"idx": 272, "label": 1}]}, {"idx": 60, "answers": [{"idx": 273, "label": 1}, {"idx": 274, "label": 1}, {"idx": 275, "label": 1}, {"idx": 276, "label": 1}]}, {"idx": 61, "answers": [{"idx": 277, "label": 1}, {"idx": 278, "label": 1}, {"idx": 279, "label": 1}, {"idx": 280, "label": 1}]}]}}
{"idx": 7, "passage": {"questions": [{"idx": 62, "answers": [{"idx": 281, "label": 0}, {"idx": 282, "label": 1}, {"idx": 283, "label": 1}, {"idx": 284, "label": 1}, {"idx": 285, "label": 0}]}, {"idx": 63, "answers": [{"idx": 286, "label": 0}, {"idx": 287, "label": 0}, {"idx": 288, "label": 0}, {"idx": 289, "label": 0}, {"idx": 290, "label": 1}]}, {"idx": 64, "answers": [{"idx": 291, "label": 0}, {"idx": 292, "label": 0}, {"idx": 293, "label": 0}, {"idx": 294, "label": 0}, {"idx": 295, "label": 0}]}, {"idx": 65, "answers": [{"idx": 296, "label": 1}, {"idx": 297, "label": 1}, {"idx": 298, "label": 1}, {"idx": 299, "label": 1}, {"idx": 300, "label": 1}]}, {"idx": 66, "answers": [{"idx": 301, "label": 1}, {"idx": 302, "label": 0}, {"idx": 303, "label": 1}, {"idx": 304, "label": 0}, {"idx": 305, "label": 1}]}, {"idx": 67, "answers": [{"idx": 306, "label": 0}, {"idx": 307, "label": 0}, {"idx": 308, "label": 0}, {"idx": 309, "label": 1}, {"idx": 310, "label": 1}]}, {"idx": 68, "answers": [{"idx": 311, "label": 0}, {"idx": 312, "label": 0}, {"idx": 313, "label": 0}, {"idx": 314, "label": 1}, {"idx": 315, "label": 0}]}, {"idx": 69, "answers": [{"idx": 316, "label": 1}, {"idx": 317, "label": 1}, {"idx": 318, "label": 1}, {"idx": 319, "label": 1}, {"idx": 320, "label": 1}]}]}}
{"idx": 8, "passage": {"questions": [{"idx": 70, "answers": [{"idx": 321, "label": 0}, {"idx": 322, "label": 0}, {"idx": 323, "label": 0}, {"idx": 324, "label": 0}]}, {"idx": 71, "answers": [{"idx": 325, "label": 1}, {"idx": 326, "label": 0}, {"idx": 327, "label": 0}, {"idx": 328, "label": 0}]}, {"idx": 72, "answers": [{"idx": 329, "label": 0}, {"idx": 330, "label": 0}, {"idx": 331, "label": 0}, {"idx": 332, "label": 0}, {"idx": 333, "label": 0}]}, {"idx": 73, "answers": [{"idx": 334, "label": 0}, {"idx": 335, "label": 0}, {"idx": 336, "label": 0}, {"idx": 337, "label": 0}, {"idx": 338, "label": 0}]}, {"idx": 74, "answers": [{"idx": 339, "label": 0}, {"idx": 340, "label": 0}, {"idx": 341, "label": 0}, {"idx": 342, "label": 1}, {"idx": 343, "label": 1}]}, {"idx": 75, "answers": [{"idx": 344, "label": 1}, {"idx": 345, "label": 1}, {"idx": 346, "label": 0}, {"idx": 347, "label": 0}, {"idx": 348, "label": 0}]}, {"idx": 76, "answers": [{"idx": 349, "label": 0}, {"idx": 350, "label": 1}, {"idx": 351, "label": 0}, {"idx": 352, "label": 0}, {"idx": 353, "label": 0}]}, {"idx": 77, "answers": [{"idx": 354, "label": 0}, {"idx": 355, "label": 0}, {"idx": 356, "label": 0}, {"idx": 357, "label": 1}, {"idx": 358, "label": 0}]}, {"idx": 78, "answers": [{"idx": 359, "label": 0}, {"idx": 360, "label": 1}, {"idx": 361, "label": 0}, {"idx": 362, "label": 0}, {"idx": 363, "label": 0}]}, {"idx": 79, "answers": [{"idx": 364, "label": 0}, {"idx": 365, "label": 0}, {"idx": 366, "label": 0}, {"idx": 367, "label": 0}, {"idx": 368, "label": 0}]}, {"idx": 80, "answers": [{"idx": 369, "label": 0}, {"idx": 370, "label": 0}, {"idx": 371, "label": 0}, {"idx": 372, "label": 0}, {"idx": 373, "label": 0}]}, {"idx": 81, "answers": [{"idx": 374, "label": 0}, {"idx": 375, "label": 0}, {"idx": 376, "label": 0}, {"idx": 377, "label": 0}, {"idx": 378, "label": 0}]}]}}
{"idx": 9, "passage": {"questions": [{"idx": 82, "answers": [{"idx": 379, "label": 0}, {"idx": 380, "label": 0}, {"idx": 381, "label": 0}, {"idx": 382, "label": 0}]}, {"idx": 83, "answers": [{"idx": 383, "label": 0}, {"idx": 384, "label": 1}, {"idx": 385, "label": 0}, {"idx": 386, "label": 0}]}, {"idx": 84, "answers": [{"idx": 387, "label": 0}, {"idx": 388, "label": 0}, {"idx": 389, "label": 0}, {"idx": 390, "label": 0}]}, {"idx": 85, "answers": [{"idx": 391, "label": 1}, {"idx": 392, "label": 0}, {"idx": 393, "label": 1}, {"idx": 394, "label": 1}]}, {"idx": 86, "answers": [{"idx": 395, "label": 0}, {"idx": 396, "label": 0}, {"idx": 397, "label": 0}, {"idx": 398, "label": 0}]}, {"idx": 87, "answers": [{"idx": 399, "label": 0}, {"idx": 400, "label": 0}, {"idx": 401, "label": 0}, {"idx": 402, "label": 1}]}, {"idx": 88, "answers": [{"idx": 403, "label": 0}, {"idx": 404, "label": 0}, {"idx": 405, "label": 1}, {"idx": 406, "label": 0}]}, {"idx": 89, "answers": [{"idx": 407, "label": 0}, {"idx": 408, "label": 0}, {"idx": 409, "label": 0}, {"idx": 410, "label": 1}]}]}}

import json
import random
# read each decoded JSON line into a list
with open('test.jsonl',encoding='utf8') as f:
data = [json.loads(line) for line in f]
# walk the structure and change the labels
for item in data:
for q in item['passage']['questions']:
for a in q['answers']:
a['label'] = random.randint(0,1)
# write each JSON line back to a new file
with open('test2.jsonl','w',encoding='utf8') as f:
for item in data:
json.dump(item,f)
print(file=f) # add a newline
You could write back to the same file, but safer to delete and rename once written successfully.

Hope this different and Fast approach will work
import json
import numpy as np
import random
def find(original, sub):
return [i+9 for i in range(len(original)) if original.startswith(sub, i)]
def split_into_parts(number, n=2):
if number % n==0:
return [int(number/2),int(number/2)]
else:
return [int(number/2),int(number/2)+1]
def get_ranodom_list(num):
o,z=split_into_parts(num,2)
ls=[0]*o+[1]*z
random.shuffle(ls)
return ls
d={"idx": 0, "passage": {"questions": [{"idx": 0, "answers": [{"idx": 0, "label": 0}, {"idx": 1, "label": 0}, {"idx": 2, "label": 0}, {"idx": 3, "label": 0}]}, {"idx": 1, "answers": [{"idx": 4, "label": 0}, {"idx": 5, "label": 0}, {"idx": 6, "label": 0}, {"idx": 7, "label": 0}]}, {"idx": 2, "answers": [{"idx": 8, "label": 1}, {"idx": 9, "label": 0}, {"idx": 10, "label": 0}, {"idx": 11, "label": 0}]}, {"idx": 3, "answers": [{"idx": 12, "label": 0}, {"idx": 13, "label": 0}, {"idx": 14, "label": 0}, {"idx": 15, "label": 0}]}, {"idx": 4, "answers": [{"idx": 16, "label": 0}, {"idx": 17, "label": 0}, {"idx": 18, "label": 0}, {"idx": 19, "label": 0}, {"idx": 20, "label": 0}]}, {"idx": 5, "answers": [{"idx": 21, "label": 0}, {"idx": 22, "label": 0}, {"idx": 23, "label": 0}, {"idx": 24, "label": 0}, {"idx": 25, "label": 0}]}, {"idx": 6, "answers": [{"idx": 26, "label": 0}, {"idx": 27, "label": 0}, {"idx": 28, "label": 0}, {"idx": 29, "label": 0}, {"idx": 30, "label": 0}]}, {"idx": 7, "answers": [{"idx": 31, "label": 0}, {"idx": 32, "label": 0}, {"idx": 33, "label": 0}, {"idx": 34, "label": 0}, {"idx": 35, "label": 0}]}, {"idx": 8, "answers": [{"idx": 36, "label": 0}, {"idx": 37, "label": 0}, {"idx": 38, "label": 0}, {"idx": 39, "label": 0}, {"idx": 40, "label": 0}]}, {"idx": 9, "answers": [{"idx": 41, "label": 0}, {"idx": 42, "label": 0}, {"idx": 43, "label": 0}, {"idx": 44, "label": 0}, {"idx": 45, "label": 0}]}]}}
original = json.dumps(d)
result=find(original,'"label": ')
num=len(result)
zo_list=get_ranodom_list(num)
temp = list(original)
counter=0
for i in range(len(original)):
if i in result:
temp[i] = str(zo_list[counter])
counter+=1
res = ''.join(temp)
print(res)

Converting JSON coordinates to numpy array

I would like to convert a JSON file back into a png image or a NumPy array.
The file JSON file consists of a list of coordinates and other metadata. As an example. it would look like this :
"firstEditDate": "2019-12-02T19:05:45.393Z",
"lastEditDate": "2020-06-30T13:21:33.371Z",
"folder": "/Pictures/poly",
"objects": [
{
"classIndex": 5,
"layer": 0,
"polygon": [
{
"x": 0,
"y": 0
},
{
"x": 1699.7291626931146,
"y": 0
},
{
"x": 1699.7291626931146,
"y": 1066.87392714095
},
{
"x": 0,
"y": 1066.87392714095
}
],
},
{
"classIndex": 2,
"layer": 0,
"polygon": [
{
"x": 844.2300556586271,
"y": 711.8243676199173
},
{
"x": 851.156462585034,
"y": 740.5194820293175
},
{
"x": 854.1249226963513,
"y": 744.477428844407
},
{
"x": 854.1249226963513,
"y": 747.4458889557243
},
(coordinates should be rounded to the nearest ones prior to creating the array or image)
The dimension of the array/ picture should be 1727 x 971
Is there any function in python that can convert the file either into an array with the value inside the array of the ClassIndex? Or into a picture where each ClassIndex is assigned to a specific color?

Here is a solution:
import matplotlib.pyplot as plt
import numpy as np
import mahotas.polygon as mp
json_dict = {
"firstEditDate": "2019-12-02T19:05:45.393Z",
"lastEditDate": "2020-06-30T13:21:33.371Z",
"folder": "/Pictures/poly",
"objects": [{
"classIndex": 1,
"layer": 0,
"polygon": [
{"x": 170, "y": 674},
{"x": 70, "y": 674},
{"x": 70, "y": 1120},
{"x": 870, "y": 1120},
{"x": 870, "y": 674},
{"x": 770, "y": 674},
{"x": 770, "y": 1020},
{"x": 170, "y": 1020},
],
}, {
"classIndex": 2,
"layer": 0,
"polygon": [
{"x": 220, "y": 870},
{"x": 220, "y": 970},
{"x": 720, "y": 970},
{"x": 720, "y": 870},
]
}, {
"classIndex": 3,
"layer": 0,
"polygon": [
{"x": 250, "y": 615},
{"x": 225, "y": 710},
{"x": 705, "y": 840},
{"x": 730, "y": 745},
]
}, {
"classIndex": 4,
"layer": 0,
"polygon": [
{"x": 350, "y": 380},
{"x": 300, "y": 465},
{"x": 730, "y": 710},
{"x": 780, "y": 630},
]
}, {
"classIndex": 5,
"layer": 0,
"polygon": [
{"x": 505, "y": 180},
{"x": 435, "y": 250},
{"x": 790, "y": 605},
{"x": 855, "y": 535},
]
}, {
"classIndex": 6,
"layer": 0,
"polygon": [
{"x": 700, "y": 30},
{"x": 615, "y": 80},
{"x": 870, "y": 515},
{"x": 950, "y": 465},
]
}]
}
canvas = np.zeros((1000,1150))
for obj in json_dict["objects"]:
pts = [(round(p["x"]),round(p["y"])) for p in obj["polygon"]]
mp.fill_polygon(pts, canvas, obj["classIndex"])
plt.imshow(canvas.transpose())
plt.colorbar()
plt.show()
Output:

Python: Json string to csv via Pandas --> ValueError: Mixing dicts with non-Series may lead to ambiguous ordering

Hello I faced problem with json string to data.frame conversion.
print (json_resp.text)
{
"error_code": 0,
"description": "",
"img_size": { "w": 650, "h": 488 },
"people": [
{
"age": 22,
"gender": 84,
"mood": 29,
"position": { "x": 190, "y": 161, "w": 259, "h": 259 },
"rotation": { "yaw": -3, "pitch": 3, "roll": -1 },
"landmarks": { "lefteye": { "x": 371, "y": 233 }, "righteye": { "x": 266, "y": 236 }, "maskpoints": [ { "x": 371, "y": 233 }, { "x": 266, "y": 236 }, { "x": 203, "y": 234 }, { "x": 206, "y": 261 }, { "x": 212, "y": 287 }, { "x": 220, "y": 313 }, { "x": 233, "y": 338 }, { "x": 250, "y": 357 }, { "x": 273, "y": 373 }, { "x": 296, "y": 388 }, { "x": 321, "y": 394 }, { "x": 346, "y": 390 }, { "x": 371, "y": 377 }, { "x": 396, "y": 362 }, { "x": 416, "y": 341 }, { "x": 430, "y": 315 }, { "x": 437, "y": 287 }, { "x": 444, "y": 258 }, { "x": 448, "y": 227 }, { "x": 215, "y": 221 }, { "x": 226, "y": 203 }, { "x": 247, "y": 195 }, { "x": 269, "y": 198 }, { "x": 291, "y": 204 }, { "x": 336, "y": 201 }, { "x": 360, "y": 193 }, { "x": 385, "y": 190 }, { "x": 408, "y": 198 }, { "x": 423, "y": 216 }, { "x": 314, "y": 231 }, { "x": 314, "y": 247 }, { "x": 314, "y": 263 }, { "x": 314, "y": 279 }, { "x": 294, "y": 297 }, { "x": 304, "y": 300 }, { "x": 315, "y": 302 }, { "x": 327, "y": 299 }, { "x": 338, "y": 297 }, { "x": 242, "y": 236 }, { "x": 254, "y": 226 }, { "x": 271, "y": 226 }, { "x": 284, "y": 240 }, { "x": 270, "y": 245 }, { "x": 253, "y": 244 }, { "x": 349, "y": 238 }, { "x": 362, "y": 224 }, { "x": 379, "y": 224 }, { "x": 393, "y": 234 }, { "x": 381, "y": 242 }, { "x": 363, "y": 242 }, { "x": 281, "y": 332 }, { "x": 294, "y": 327 }, { "x": 306, "y": 322 }, { "x": 315, "y": 325 }, { "x": 325, "y": 323 }, { "x": 340, "y": 328 }, { "x": 357, "y": 335 }, { "x": 341, "y": 347 }, { "x": 327, "y": 354 }, { "x": 317, "y": 354 }, { "x": 306, "y": 353 }, { "x": 294, "y": 347 }, { "x": 289, "y": 333 }, { "x": 306, "y": 331 }, { "x": 316, "y": 332 }, { "x": 325, "y": 331 }, { "x": 349, "y": 334 }, { "x": 326, "y": 339 }, { "x": 316, "y": 340 }, { "x": 306, "y": 339 } ] },
"clothingcolors": [ ],
"ethnicity": { "african": 83, "asian": 0, "caucasian": 12, "hispanic": 3 },
"emotions": { "happiness": 1, "surprise": 5, "anger": 2, "disgust": 2, "fear": 1, "sadness": 11 }
}
]
However, when I try to change json string to data.frame I got:
import pandas as pd
df_json = pd.read_json(json_resp.text, typ='frame')
print (df_json)
Traceback (most recent call last):
File "<input>", line 1, in <module>
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\io\json\json.py", line 427, in read_json
result = json_reader.read()
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\io\json\json.py", line 537, in read
obj = self._get_object_parser(self.data)
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\io\json\json.py", line 556, in _get_object_parser
obj = FrameParser(json, **kwargs).parse()
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\io\json\json.py", line 652, in parse
self._parse_no_numpy()
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\io\json\json.py", line 871, in _parse_no_numpy
loads(json, precise_float=self.precise_float), dtype=None)
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\core\frame.py", line 392, in __init__
mgr = init_dict(data, index, columns, dtype=dtype)
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\core\internals\construction.py", line 212, in init_dict
return arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\core\internals\construction.py", line 51, in arrays_to_mgr
index = extract_index(arrays)
File "C:\Users\uzytkownik\PycharmProjects\Face API\venv\lib\site-packages\pandas\core\internals\construction.py", line 320, in extract_index
raise ValueError('Mixing dicts with non-Series may lead to '
ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.
What shall I change in code to obtain simple data.frame?

json_normalize is what you would want to do. However, there are nested lists within which means it only normalizes/flattens out to first level.
I think the issue comes in with the landmarks.maskpoints as that creates 70 rows with 2 columns x, and y. So trying to create a single row, WITH something that contains 70 rows could be an issue.
You can sort of see what I mean if you just start trying to unwrap/flatten it little by little. Essentially to flatten, you want to normalize each part, then at the end merge them all together into a single row, but you can see what the issue is with the maskpoints.
jsonStr = '''
{
"error_code": 0,
"description": "",
"img_size": { "w": 650, "h": 488 },
"people": [
{
"age": 22,
"gender": 84,
"mood": 29,
"position": { "x": 190, "y": 161, "w": 259, "h": 259 },
"rotation": { "yaw": -3, "pitch": 3, "roll": -1 },
"landmarks": { "lefteye": { "x": 371, "y": 233 }, "righteye": { "x": 266, "y": 236 }, "maskpoints": [ { "x": 371, "y": 233 }, { "x": 266, "y": 236 }, { "x": 203, "y": 234 }, { "x": 206, "y": 261 }, { "x": 212, "y": 287 }, { "x": 220, "y": 313 }, { "x": 233, "y": 338 }, { "x": 250, "y": 357 }, { "x": 273, "y": 373 }, { "x": 296, "y": 388 }, { "x": 321, "y": 394 }, { "x": 346, "y": 390 }, { "x": 371, "y": 377 }, { "x": 396, "y": 362 }, { "x": 416, "y": 341 }, { "x": 430, "y": 315 }, { "x": 437, "y": 287 }, { "x": 444, "y": 258 }, { "x": 448, "y": 227 }, { "x": 215, "y": 221 }, { "x": 226, "y": 203 }, { "x": 247, "y": 195 }, { "x": 269, "y": 198 }, { "x": 291, "y": 204 }, { "x": 336, "y": 201 }, { "x": 360, "y": 193 }, { "x": 385, "y": 190 }, { "x": 408, "y": 198 }, { "x": 423, "y": 216 }, { "x": 314, "y": 231 }, { "x": 314, "y": 247 }, { "x": 314, "y": 263 }, { "x": 314, "y": 279 }, { "x": 294, "y": 297 }, { "x": 304, "y": 300 }, { "x": 315, "y": 302 }, { "x": 327, "y": 299 }, { "x": 338, "y": 297 }, { "x": 242, "y": 236 }, { "x": 254, "y": 226 }, { "x": 271, "y": 226 }, { "x": 284, "y": 240 }, { "x": 270, "y": 245 }, { "x": 253, "y": 244 }, { "x": 349, "y": 238 }, { "x": 362, "y": 224 }, { "x": 379, "y": 224 }, { "x": 393, "y": 234 }, { "x": 381, "y": 242 }, { "x": 363, "y": 242 }, { "x": 281, "y": 332 }, { "x": 294, "y": 327 }, { "x": 306, "y": 322 }, { "x": 315, "y": 325 }, { "x": 325, "y": 323 }, { "x": 340, "y": 328 }, { "x": 357, "y": 335 }, { "x": 341, "y": 347 }, { "x": 327, "y": 354 }, { "x": 317, "y": 354 }, { "x": 306, "y": 353 }, { "x": 294, "y": 347 }, { "x": 289, "y": 333 }, { "x": 306, "y": 331 }, { "x": 316, "y": 332 }, { "x": 325, "y": 331 }, { "x": 349, "y": 334 }, { "x": 326, "y": 339 }, { "x": 316, "y": 340 }, { "x": 306, "y": 339 } ] },
"clothingcolors": [ ],
"ethnicity": { "african": 83, "asian": 0, "caucasian": 12, "hispanic": 3 },
"emotions": { "happiness": 1, "surprise": 5, "anger": 2, "disgust": 2, "fear": 1, "sadness": 11 }
}
]
}'''
import json
from pandas.io.json import json_normalize
jsonObj = json.loads(jsonStr)
# flatten at 1st level. But still nested lists/dictionaries in column `people`
df_a = json_normalize(jsonObj)
# so flatten out people, and you'll see clothingcolors still has a list and landmarks too
df_people = json_normalize(jsonObj['people'])
df_clothingcolors = json_normalize(jsonObj['people'][0]['clothingcolors'])
df_landmarks = json_normalize(jsonObj['people'][0]['landmarks'])
# the landmarks column still need to flatten maskpoints...but maskpoints produces 70 rows, and there's your issue
df_maskpoints = json_normalize(jsonObj['people'][0]['landmarks']['maskpoints'])
So if you look at the shape of these:
print (df_a.shape)
(1, 5)
print (df_people.shape)
(1, 26)
print (df_clothingcolors.shape)
(0, 0)
print (df_landmarks.shape)
(1, 5)
print (df_maskpoints.shape)
(70, 2)
...you see the maskpoints shape is 70 rows.
BUT,
I found this blog useful. Essentially it unwraps all those nested lists so that you end up with 1 big flat table.
jsonStr = '''
{
"error_code": 0,
"description": "",
"img_size": { "w": 650, "h": 488 },
"people": [
{
"age": 22,
"gender": 84,
"mood": 29,
"position": { "x": 190, "y": 161, "w": 259, "h": 259 },
"rotation": { "yaw": -3, "pitch": 3, "roll": -1 },
"landmarks": { "lefteye": { "x": 371, "y": 233 }, "righteye": { "x": 266, "y": 236 }, "maskpoints": [ { "x": 371, "y": 233 }, { "x": 266, "y": 236 }, { "x": 203, "y": 234 }, { "x": 206, "y": 261 }, { "x": 212, "y": 287 }, { "x": 220, "y": 313 }, { "x": 233, "y": 338 }, { "x": 250, "y": 357 }, { "x": 273, "y": 373 }, { "x": 296, "y": 388 }, { "x": 321, "y": 394 }, { "x": 346, "y": 390 }, { "x": 371, "y": 377 }, { "x": 396, "y": 362 }, { "x": 416, "y": 341 }, { "x": 430, "y": 315 }, { "x": 437, "y": 287 }, { "x": 444, "y": 258 }, { "x": 448, "y": 227 }, { "x": 215, "y": 221 }, { "x": 226, "y": 203 }, { "x": 247, "y": 195 }, { "x": 269, "y": 198 }, { "x": 291, "y": 204 }, { "x": 336, "y": 201 }, { "x": 360, "y": 193 }, { "x": 385, "y": 190 }, { "x": 408, "y": 198 }, { "x": 423, "y": 216 }, { "x": 314, "y": 231 }, { "x": 314, "y": 247 }, { "x": 314, "y": 263 }, { "x": 314, "y": 279 }, { "x": 294, "y": 297 }, { "x": 304, "y": 300 }, { "x": 315, "y": 302 }, { "x": 327, "y": 299 }, { "x": 338, "y": 297 }, { "x": 242, "y": 236 }, { "x": 254, "y": 226 }, { "x": 271, "y": 226 }, { "x": 284, "y": 240 }, { "x": 270, "y": 245 }, { "x": 253, "y": 244 }, { "x": 349, "y": 238 }, { "x": 362, "y": 224 }, { "x": 379, "y": 224 }, { "x": 393, "y": 234 }, { "x": 381, "y": 242 }, { "x": 363, "y": 242 }, { "x": 281, "y": 332 }, { "x": 294, "y": 327 }, { "x": 306, "y": 322 }, { "x": 315, "y": 325 }, { "x": 325, "y": 323 }, { "x": 340, "y": 328 }, { "x": 357, "y": 335 }, { "x": 341, "y": 347 }, { "x": 327, "y": 354 }, { "x": 317, "y": 354 }, { "x": 306, "y": 353 }, { "x": 294, "y": 347 }, { "x": 289, "y": 333 }, { "x": 306, "y": 331 }, { "x": 316, "y": 332 }, { "x": 325, "y": 331 }, { "x": 349, "y": 334 }, { "x": 326, "y": 339 }, { "x": 316, "y": 340 }, { "x": 306, "y": 339 } ] },
"clothingcolors": [ ],
"ethnicity": { "african": 83, "asian": 0, "caucasian": 12, "hispanic": 3 },
"emotions": { "happiness": 1, "surprise": 5, "anger": 2, "disgust": 2, "fear": 1, "sadness": 11 }
}
]
}'''
import json
from pandas.io.json import json_normalize
def flatten_json(y):
out = {}
def flatten(x, name=''):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + '_')
elif type(x) is list:
i = 0
for a in x:
flatten(a, name + str(i) + '_')
i += 1
else:
out[name[:-1]] = x
flatten(y)
return out
jsonObj = json.loads(jsonStr)
flat = flatten_json(jsonObj)
df = json_normalize(flat)
The output will be your 1 row, with 168 columns.

Python: change json outcome into data.frame

I have got json object after connection via Python to F.A.C.E API and analysis of one of face image.
I am newbie in python and my question is:
How to transform json object into data.frame and then into .xls/.csv?
print ('Response : ', json_resp.text)
#Console print:
Response : {
"error_code": 0,
"description": "",
"img_size": { "w": 650, "h": 488 },
"people": [
{
"age": 22,
"gender": 84,
"mood": 29,
"position": { "x": 190, "y": 161, "w": 259, "h": 259 },
"rotation": { "yaw": -3, "pitch": 3, "roll": -1 },
"landmarks": { "lefteye": { "x": 371, "y": 233 }, "righteye": { "x": 266, "y": 236 }, "maskpoints": [ { "x": 371, "y": 233 }, { "x": 266, "y": 236 }, { "x": 203, "y": 234 }, { "x": 206, "y": 261 }, { "x": 212, "y": 287 }, { "x": 220, "y": 313 }, { "x": 233, "y": 338 }, { "x": 250, "y": 357 }, { "x": 273, "y": 373 }, { "x": 296, "y": 388 }, { "x": 321, "y": 394 }, { "x": 346, "y": 390 }, { "x": 371, "y": 377 }, { "x": 396, "y": 362 }, { "x": 416, "y": 341 }, { "x": 430, "y": 315 }, { "x": 437, "y": 287 }, { "x": 444, "y": 258 }, { "x": 448, "y": 227 }, { "x": 215, "y": 221 }, { "x": 226, "y": 203 }, { "x": 247, "y": 195 }, { "x": 269, "y": 198 }, { "x": 291, "y": 204 }, { "x": 336, "y": 201 }, { "x": 360, "y": 193 }, { "x": 385, "y": 190 }, { "x": 408, "y": 198 }, { "x": 423, "y": 216 }, { "x": 314, "y": 231 }, { "x": 314, "y": 247 }, { "x": 314, "y": 263 }, { "x": 314, "y": 279 }, { "x": 294, "y": 297 }, { "x": 304, "y": 300 }, { "x": 315, "y": 302 }, { "x": 327, "y": 299 }, { "x": 338, "y": 297 }, { "x": 242, "y": 236 }, { "x": 254, "y": 226 }, { "x": 271, "y": 226 }, { "x": 284, "y": 240 }, { "x": 270, "y": 245 }, { "x": 253, "y": 244 }, { "x": 349, "y": 238 }, { "x": 362, "y": 224 }, { "x": 379, "y": 224 }, { "x": 393, "y": 234 }, { "x": 381, "y": 242 }, { "x": 363, "y": 242 }, { "x": 281, "y": 332 }, { "x": 294, "y": 327 }, { "x": 306, "y": 322 }, { "x": 315, "y": 325 }, { "x": 325, "y": 323 }, { "x": 340, "y": 328 }, { "x": 357, "y": 335 }, { "x": 341, "y": 347 }, { "x": 327, "y": 354 }, { "x": 317, "y": 354 }, { "x": 306, "y": 353 }, { "x": 294, "y": 347 }, { "x": 289, "y": 333 }, { "x": 306, "y": 331 }, { "x": 316, "y": 332 }, { "x": 325, "y": 331 }, { "x": 349, "y": 334 }, { "x": 326, "y": 339 }, { "x": 316, "y": 340 }, { "x": 306, "y": 339 } ] },
"clothingcolors": [ ],
"ethnicity": { "african": 83, "asian": 0, "caucasian": 12, "hispanic": 3 },
"emotions": { "happiness": 1, "surprise": 5, "anger": 2, "disgust": 2, "fear": 1, "sadness": 11 }
}
]
}
I would like to obtain data frame like:
error_code, age, gender, mood, (...), emotions.sadness
0 0, 0, 84, 29, (...), 11
and then
.xls or .csv in "C://Users"

You could use the methods pandas.read_json and Dataframe.to_csv:
import pandas
df = pandas.read_json(json_resp.tex, typ='frame')
df.to_csv("path_to_your_file.csv")

Python dictionary changes when using intermediate variable

I'm feeding a function a string, which reads the string char by char. Based on the char being worked on, a JSON template is called from a dictionary, edited slightly and saved to a final dictionary, which will be parsed to JSON and saved.
The problem is that this template dictionary should stay constant, but it doesn't. Somehow, the values I write to the intermediate variable gets saved to the original template dictionary, messing up the subsequent data I'm trying to save.
Am I missing some basic concept of the dictionary? This is my first time working with dictionaries to such an extent so I wouldn't even be surprised.
The template dictionary:
self.map_legend = {"#": {"Id": 100, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Wall", "PlayerNumber": 0},
"-": {"Id": 200, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Shield", "PlayerNumber": 0},
"x": {"Id": 300, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Alien", "PlayerNumber": 0},
"|": {"Id": 400, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "AlienBullet", "PlayerNumber": 0},
"!": {"Id": 500, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Missile", "PlayerNumber": 0},
"i": {"Id": 500, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Missile", "PlayerNumber": 1},
"M": {"Id": 600, "Alive": False, "X": 0, "Y": 0, "Width": 3, "Height": 1, "Type": "MissileController", "PlayerNumber": 0},
"X": {"Id": 700, "Alive": False, "X": 0, "Y": 0, "Width": 3, "Height": 1, "Type": "AlienFactory", "PlayerNumber": 0},
"A": {"Id": 800, "Alive": False, "X": 0, "Y": 0, "Width": 3, "Height": 1, "Type": "Ship", "PlayerNumber": 0},
"V": {"Id": 800, "Alive": False, "X": 0, "Y": 0, "Width": 3, "Height": 1, "Type": "Ship", "PlayerNumber": 1},
" ": {"Id": 900, "Alive": False, "X": 0, "Y": 0, "Width": 1, "Height": 1, "Type": "Space", "PlayerNumber": 0}}
The problem code:
for char in self.initial_game_map:
if char != "\n":
element = self.map_legend[char]
self.id_counters[char] += 1
element["Id"] = self.id_counters[char] + element["Id"]
element["Alive"] = True
element["X"] = char_counter % self.state_json["Map"]["Height"]
element["Y"] = char_counter / self.state_json["Map"]["Height"]
print self.map_legend[char]
print element
row.append(element)
element = {}
char_counter += 1
else:
self.state_json["Map"]["Rows"].append(row)
row = []
Some output:
V
{'Width': 3, 'PlayerNumber': 1, 'Y': 1, 'X': 2, 'Type': 'Ship', 'Id': 801, 'Alive': True, 'Height': 1}
{'Width': 3, 'PlayerNumber': 1, 'Y': 1, 'X': 2, 'Type': 'Ship', 'Id': 801, 'Alive': True, 'Height': 1}
#
{'Width': 1, 'PlayerNumber': 0, 'Y': 0, 'X': 18, 'Type': 'Wall', 'Id': 103, 'Alive': True, 'Height': 1}
{'Width': 1, 'PlayerNumber': 0, 'Y': 0, 'X': 18, 'Type': 'Wall', 'Id': 103, 'Alive': True, 'Height': 1}
the element variable is behaving as its supposed to, but you can see that self.map_legend assumes the value of element for some reason after element is changed, which is NOT what I want. What's going on?

element and self.map_legend[char] point to the same dictionary and thus if you update element you will update the values of the dictionary self.map_legend[char]. You seem to want a copy so use:
element = self.map_legend[char].copy()
Reference in the python documentation: https://docs.python.org/2/library/copy.html. As the dictionaries are shallow you don't need .deepcopy()

You need to deepcopy the dictionary, else the original will get modified.
from copy import deepcopy
element = deepcopy(self.map_legend[char])

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