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將來自 API 服務的嵌套 JSON 響應解析為 python 中的 csv

[英]Parse nested JSON response from API service into csv in python

我試圖以清晰有序的方式將 API 響應的輸出保存到 CSV 文件中,但沒有運氣,這是檢索 API 數據的腳本:

import json
import requests
import csv

# List of keywords to be checked
keywords = open("/test.txt", encoding="ISO-8859-1")

keywords_to_check = []

try:
    for keyword in keywords:
        keyword = keyword.replace("\n", "")
        keywords_to_check.append(keyword)
except Exception:
        print("An error occurred. I will try again!")
        pass

apikey = # my api key
apiurl = # api url
apiparams = {
    'apikey': apikey, 
    'keyword': json.dumps(keywords_to_check), 
    'metrics_location': '2840',
    'metrics_language': 'en',
    'metrics_network': 'googlesearchnetwork',
    'metrics_currency': 'USD',
    'output': 'csv'
}
response = requests.post(apiurl, data=apiparams)
jsonize = json.dumps(response.json(), indent=4, sort_keys=True)

if response.status_code == 200:
    print(json.dumps(response.json(), indent=4, sort_keys=True))

我得到的輸出如下:

{
    "results": {
        "bin": {
            "cmp": 0.795286539,
            "cpc": 3.645033,
            "m1": 110000,
            "m10": 90500,
            "m10_month": 2,
            "m10_year": 2019,
            "m11": 135000,
            "m11_month": 1,
            "m11_year": 2019,
            "m12": 135000,
            "m12_month": 12,
            "m12_year": 2018,
            "m1_month": 11,
            "m1_year": 2019,
            "m2": 110000,
            "m2_month": 10,
            "m2_year": 2019,
            "m3": 110000,
            "m3_month": 9,
            "m3_year": 2019,
            "m4": 135000,
            "m4_month": 8,
            "m4_year": 2019,
            "m5": 135000,
            "m5_month": 7,
            "m5_year": 2019,
            "m6": 110000,
            "m6_month": 6,
            "m6_year": 2019,
            "m7": 110000,
            "m7_month": 5,
            "m7_year": 2019,
            "m8": 90500,
            "m8_month": 4,
            "m8_year": 2019,
            "m9": 90500,
            "m9_month": 3,
            "m9_year": 2019,
            "string": "bin",
            "volume": 110000
        },
        "chair": {
            "cmp": 1,
            "cpc": 1.751945,
            "m1": 1000000,
            "m10": 823000,
            "m10_month": 2,
            "m10_year": 2019,
            "m11": 1500000,
            "m11_month": 1,
            "m11_year": 2019,
            "m12": 1500000,
            "m12_month": 12,
            "m12_year": 2018,
            "m1_month": 11,
            "m1_year": 2019,
            "m2": 1000000,
            "m2_month": 10,
            "m2_year": 2019,
            "m3": 1000000,
            "m3_month": 9,
            "m3_year": 2019,
            "m4": 1220000,
            "m4_month": 8,
            "m4_year": 2019,
            "m5": 1220000,
            "m5_month": 7,
            "m5_year": 2019,
            "m6": 1000000,
            "m6_month": 6,
            "m6_year": 2019,
            "m7": 1000000,
            "m7_month": 5,
            "m7_year": 2019,
            "m8": 1000000,
            "m8_month": 4,
            "m8_year": 2019,
            "m9": 1000000,
            "m9_month": 3,
            "m9_year": 2019,
            "string": "chair",
            "volume": 1220000
        }, ....

我想要實現的是一個 csv 文件,顯示以下信息和排序,列是 string、cmp、cpc 和 volume:

字符串;cmp;每次點擊費用;音量
斌;0.795286539;3.645033;110000
椅子;1;1.751945;1220000

根據 Sidous 的建議,我得出以下結論:

import pandas as pd
data = response.json()
df = pd.DataFrame.from_dict(data)
df.head()

哪個游戲我有以下輸出:

結果
bin {'string': 'bin', 'volume': 110000, 'm1': 1100 ...
椅子{'字符串':'椅子','音量':1220000,'m1':1 ...
花{'字符串':'花','體積':1830000,'m1':...
表{'字符串':'表','體積':673000,'m1':82 ...
水{'字符串':'水','體積':673000,'m1':67 ...

關閉,但仍然如何將“字符串”、“音量”等顯示為列並避免顯示字典的 { ?

非常感謝誰能幫我解決這個問題:)

歪斜

我建議將響應保存在 Pandas 數據框中,然后由 Pandas 存儲(你知道 csv 文件很容易被 Pandas 處理)。

import pandas as pd


# receiving results in a dictionary
dic = response.json()

# remove the results key from the dictionary
dic = dic.pop("results", None)

# convert dictionary to dataframe
data = pd.DataFrame.from_dict(dic, orient='index')

# string;cmp;cpc;volume
new_data = pd.concat([data['string'], data['cmp'], data['cpc'], data['volume']], axis=1)

# removing the default index (bin and chair keys)
new_data.reset_index(drop=True, inplace=True)

print(new_data)

# saving new_data into a csv file
new_data.to_csv('name_of_file.csv')

你可以在 python 文件的同一目錄中找到 csv 文件(否則你可以在 .to_csv() 方法中指定它)。

您可以在下面的屏幕截圖中看到最終結果。

在此處輸入圖片說明

使用with open命令打開一個文本文件with open並通過遍歷整個dict進一步寫下數據

with open("text.csv", "w+") as f:
    f.write('string;cmp;cpc;volume\n')
    for res in response.values():     #This is after I assumed that `response` is of type dict
        for r in res.values():
            f.write(r['string']+';'+str(r['cmp'])+';'+str(r['cpc'])+';'+str(r['volume'])+'\n')

嘗試這個:

import pandas as pd

data = response.json()
cleaned_data = []

for key, val in data["results"].items():
    cleaned_data.append(val)

df = pd.DataFrame.from_dict(cleaned_data)
df1 = df[["string","cmp","cpc","volume"]]
df1.head()
df1.to_csv("output.csv")

使用csv.DictWriter怎么樣,因為您的數據幾乎是它需要的功能?

import csv

if __name__ is "__main__":
  results = {"chair": {"cmp": 1, "cpc": 3.64}, "bin": {"cmp": 0.5, "cpc": 1.75}} # two rows will do for the example
  # Now let's get the data structure we really want: a list of rows
  rows = []
  for key, value in results:
    rows.append(results)
    # And, while we're at it, set the string part
    rows[-1]["string"] = key

  # Create the header
  fieldnames = set()
  for row in rows:
    for fname in row:
      fieldnames.add(fname)

  # Write to the file
  with open("mycsv.csv", "w", newline="") as file_:
    writer = csv.DictWriter(file_, fieldnames=fieldnames)
    writer.writeheader()
    for row in rows:
      writer.writerow(row)

你應該擅長這種東西,不使用任何其他庫

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