通過 Python 將 JSON 轉換為 CSV

Question

我有一個 JSON object 格式如下。 本質上，它們是一些產品信息。

{

      "6923492595127": {
        "upcName": {
          "en": "1",
          "hi": "",
          "ja": "",
          "zh": ""
        },
        "productName": {
          "en": "Excellence",
          "hi": "",
          "ja": "",
          "zh": ""
        },
        "thumbnailImageUrl": null,
        "heroImageUrl": null,
        "swatchImageUrl": null,
        "shadeArray": [
          {
            "histogram": {
              "r": "0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 0 58 59 60 61 62 63 64 0 66 67 68 0 70 0 72 73 0 75 0 77 78 79 80 81 0 83 0 85 86 87 88 0 90 0 92 93 0 95 0 0 98 0 100 101 0 103 104 0 106 0 108 109 0 111 0 113 0 115 116 0 0 119 0 121 0 123 124 0 126 0 0 0 0 0 132 133 134 135 0 0 0 0 140 141 142 0 0 145 146 147 0 0 150 0 0 153 0 0 0 157 0 0 160 161 0 0 0 165 0 0 0 0 0 0 172 0 0 0 0 0 0 0 0 0 182 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "g": "0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 0 58 59 60 61 62 63 64 0 66 67 68 0 70 0 72 73 0 75 0 77 78 79 80 81 0 83 0 85 86 87 88 0 90 0 92 93 0 95 0 0 98 0 100 101 0 103 104 0 106 0 108 109 0 111 0 113 0 115 116 0 0 119 0 121 0 123 124 0 126 0 0 0 0 0 132 133 134 135 0 0 0 0 140 141 142 0 0 145 146 147 0 0 150 0 0 153 0 0 0 157 0 0 160 161 0 0 0 165 0 0 0 0 0 0 172 0 0 0 0 0 0 0 0 0 182 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "b": "0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 0 58 59 60 61 62 63 64 0 66 67 68 0 70 0 72 73 0 75 0 77 78 79 80 81 0 83 0 85 86 87 88 0 90 0 92 93 0 95 0 0 98 0 100 101 0 103 104 0 106 0 108 109 0 111 0 113 0 115 116 0 0 119 0 121 0 123 124 0 126 0 0 0 0 0 132 133 134 135 0 0 0 0 140 141 142 0 0 145 146 147 0 0 150 0 0 153 0 0 0 157 0 0 160 161 0 0 0 165 0 0 0 0 0 0 172 0 0 0 0 0 0 0 0 0 182 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "c": "61484 41185 37054 36648 27046 28373 27107 26508 13034 20094 20425 18989 11940 11254 10920 10084 9373 9214 8437 8326 4030 7893 7688 3781 6739 3298 6865 6022 2890 2945 5707 2748 2616 4846 2386 2138 1908 1920 1749 3485 1566 1597 1582 1524 1448 1443 1341 1275 1231 1134 1041 953 863 912 893 812 766 0 734 715 683 601 596 534 511 0 456 446 377 0 747 0 308 265 0 286 0 256 236 207 197 188 0 156 0 159 115 138 94 0 123 0 82 112 0 162 0 0 146 0 75 43 0 39 28 0 46 0 33 28 0 16 0 30 0 23 16 0 0 28 0 16 0 10 25 0 10 0 0 0 0 0 8 18 5 7 0 0 0 0 6 5 3 0 0 3 3 3 0 0 4 0 0 2 0 0 0 3 0 0 2 1 0 0 0 4 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "totalpixels": 549705
            },
            "intensity": 0.8,
            "shine": 0,
            "effect": 0,
            "family": "",
            "blendGradientTopOffset": 0,
            "blendGradientBottomOffset": 0,
            "warning_type": null
          }
        ]
      },
      "6923492597510": {
        "upcName": {
          "en": "3",
          "hi": "",
          "ja": "",
          "zh": ""
        },
        "productName": {
          "en": "Excellence",
          "hi": "",
          "ja": "",
          "zh": ""
        },
        "thumbnailImageUrl": null,
        "heroImageUrl": null,
        "swatchImageUrl": null,
        "shadeArray": [
          {
            "histogram": {
              "r": "0 4 7 10 13 16 18 21 22 24 26 27 0 30 31 33 0 34 36 0 38 0 40 41 0 44 46 0 48 49 0 51 0 53 55 0 57 0 59 0 61 63 0 65 0 68 0 69 0 72 0 74 75 0 0 78 80 0 0 82 0 85 0 88 0 90 0 91 0 93 0 96 0 98 0 100 0 101 0 104 0 106 0 0 110 0 112 0 114 115 0 0 118 119 0 0 122 123 0 0 125 0 126 0 0 131 0 0 134 134 0 0 139 0 0 139 0 0 144 0 146 0 0 0 150 0 152 0 0 156 158 156 0 0 160 0 0 0 0 0 0 0 174 169 172 0 0 174 0 0 0 0 0 181 0 184 0 183 0 0 188 0 188 191 0 0 0 196 0 0 0 0 0 200 0 205 0 0 0 0 0 210 0 214 0 0 0 220 0 0 0 0 0 0 0 0 0 0 0 0 229 0 0 0 0 0 0 0 0 0 0 243 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "g": "0 0 0 0 0 0 0 0 2 3 5 6 0 8 9 10 0 12 13 0 15 0 16 18 0 19 21 0 22 24 0 26 0 27 29 0 30 0 32 0 34 35 0 37 0 39 0 41 0 43 0 44 46 0 0 49 50 0 0 53 0 55 0 57 0 59 0 61 0 63 0 65 0 67 0 69 0 71 0 73 0 75 0 0 77 0 79 0 81 83 0 0 86 86 0 0 90 90 0 0 94 0 96 0 0 99 0 0 103 103 0 0 105 0 0 109 0 0 112 0 114 0 0 0 118 0 121 0 0 124 124 124 0 0 129 0 0 0 0 0 0 0 136 137 138 0 0 141 0 0 0 0 0 149 0 149 0 152 0 0 155 0 155 157 0 0 0 159 0 0 0 0 0 168 0 167 0 0 0 0 0 173 0 179 0 0 0 181 0 0 0 0 0 0 0 0 0 0 0 0 197 0 0 0 0 0 0 0 0 0 0 208 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "b": "0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 0 4 5 0 6 0 8 9 0 11 12 0 13 15 0 16 0 18 19 0 21 0 22 0 24 26 0 27 0 29 0 31 0 32 0 34 36 0 0 38 39 0 0 41 0 43 0 45 0 47 0 49 0 50 0 52 0 54 0 56 0 59 0 60 0 62 0 0 64 0 66 0 68 70 0 0 73 74 0 0 76 78 0 0 81 0 85 0 0 85 0 0 89 91 0 0 92 0 0 97 0 0 98 0 100 0 0 0 103 0 106 0 0 107 109 113 0 0 115 0 0 0 0 0 0 0 116 123 122 0 0 126 0 0 0 0 0 131 0 133 0 138 0 0 138 0 143 140 0 0 0 145 0 0 0 0 0 150 0 153 0 0 0 0 0 159 0 157 0 0 0 161 0 0 0 0 0 0 0 0 0 0 0 0 173 0 0 0 0 0 0 0 0 0 0 183 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "c": "492493 5608 5037 4811 4046 1920 3528 1706 1566 1597 1582 1524 0 1448 1443 1341 0 1275 1231 0 1134 0 1041 953 0 863 912 0 893 812 0 766 0 734 715 0 683 0 601 0 596 534 0 511 0 456 0 446 0 377 0 386 361 0 0 308 265 0 0 286 0 256 0 236 0 207 0 197 0 188 0 156 0 159 0 115 0 138 0 94 0 123 0 0 82 0 112 0 90 72 0 0 81 65 0 0 75 43 0 0 39 0 28 0 0 46 0 0 33 28 0 0 16 0 0 30 0 0 23 0 16 0 0 0 28 0 16 0 0 10 15 10 0 0 10 0 0 0 0 0 0 0 8 8 15 0 0 7 0 0 0 0 0 6 0 5 0 3 0 0 3 0 3 3 0 0 0 4 0 0 0 0 0 2 0 3 0 0 0 0 0 2 0 1 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0",
              "totalpixels": 549705
            },
            "intensity": 0.791413,
            "shine": 0,
            "effect": 0,
            "family": "",
            "blendGradientTopOffset": 0,
            "blendGradientBottomOffset": 0,
            "warning_type": null
          }
        ]
      }
}

我想將它們轉換為具有以下標題和行的 CSV。

+ID+--+upcName_en+...+productName_en+...+thumbnailImageUrl+heroImageUrl+swatchImageUrl+shadeArray_histogram_r+...+shadeArray_intensity+...+shadeArray_warning_type

+6923492595127+1+Excellence+...+null+null+null+0 1 2 3 4 5 6 7 8 9 10...+0.8+...+null
+6923492597510+3+Excellence+...+null+null+null+0 1 2 3 4 5 6 7 8 9 10...+0.8+...+null

我嘗試使用從其他鏈接引用的以下代碼來展平 JSON，但結果不是我想要的。

import pandas
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

# Opening JSON file

filename = 'somefile'

with open(filename+'.json', encoding='utf8') as file:
    data = json.load(file)
    file.close()

flat = flatten_json(data)



with open(filename+'.csv', 'w') as output :
    for (k,v) in flat.items() :
        try :
            output.write(k + ' | ' + v + '\n')
        except :
            output.write(k + ' | ' + '\n')
    output.close()

Answer 1

您可以遍歷 JSON 並將數據逐行添加到 CSV ：

import csv
import json

with open('data.json', 'r') as f:
    data = json.load(f)

with open('result.csv', 'w', newline='') as f:
    w = csv.writer(f)
    for product_id, product in data.items():
        w.writerow([product_id,
                    product['upcName']['en'],
                    product['productName']['en'],
                    product['thumbnailImageUrl'],
                    product['heroImageUrl'],
                    product['swatchImageUrl'],
                    product['shadeArray'][0]['histogram']['r'],
                    product['shadeArray'][0]['intensity'],
                    product['shadeArray'][0]['warning_type']])

Output：

6923492595127,1,Excellence,,,,0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 0 58 59 60 61 62 63 64 0 66 67 68 0 70 0 72 73 0 75 0 77 78 79 80 81 0 83 0 85 86 87 88 0 90 0 92 93 0 95 0 0 98 0 100 101 0 103 104 0 106 0 108 109 0 111 0 113 0 115 116 0 0 119 0 121 0 123 124 0 126 0 0 0 0 0 132 133 134 135 0 0 0 0 140 141 142 0 0 145 146 147 0 0 150 0 0 153 0 0 0 157 0 0 160 161 0 0 0 165 0 0 0 0 0 0 172 0 0 0 0 0 0 0 0 0 182 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0,0.8,
6923492597510,3,Excellence,,,,0 4 7 10 13 16 18 21 22 24 26 27 0 30 31 33 0 34 36 0 38 0 40 41 0 44 46 0 48 49 0 51 0 53 55 0 57 0 59 0 61 63 0 65 0 68 0 69 0 72 0 74 75 0 0 78 80 0 0 82 0 85 0 88 0 90 0 91 0 93 0 96 0 98 0 100 0 101 0 104 0 106 0 0 110 0 112 0 114 115 0 0 118 119 0 0 122 123 0 0 125 0 126 0 0 131 0 0 134 134 0 0 139 0 0 139 0 0 144 0 146 0 0 0 150 0 152 0 0 156 158 156 0 0 160 0 0 0 0 0 0 0 174 169 172 0 0 174 0 0 0 0 0 181 0 184 0 183 0 0 188 0 188 191 0 0 0 196 0 0 0 0 0 200 0 205 0 0 0 0 0 210 0 214 0 0 0 220 0 0 0 0 0 0 0 0 0 0 0 0 229 0 0 0 0 0 0 0 0 0 0 243 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0,0.791413,