在Pandas Dataframe上迭代Google分析API函数

I have a Dataframe (f) of inputs: Page Title (title_), Start date ('date_') and End date (date_date), and I want to iterate The Google analytics API get_report function on every row in the DataFrame, to get a new DataFrame of the results.

我有一个输入的数据帧(f):页面标题(title_),开始日期('date_')和结束日期(date_date),我想在DataFrame的每一行上迭代Google分析API get_report函数,以获得一个新的DataFrame结果。

Here is my Code:

这是我的代码:

for i in f.index:
    lista = []
    df = print_response(get_report(
             config.service,  
             start_date=[f.loc[i]['date_']],
             end_date=[f.loc[i]['date_date']], 
             view_id='xxxxxxxx',
             metrics=[{'expression': 'ga:pageViews'}],
             dimensionFilterClauses= [{
                      "filters": [{
                              "dimensionName": "ga:pageTitle",
                              "expressions": [f.loc[i]['title_']]}]
              }],
             dimensions=[{"name": "ga:pageTitle"}]))
    lista.append(df)
    time.sleep(2)
print(lista)

I get the error:

我收到错误:

TypeError: Object of type 'date' is not JSON serializable

TypeError:“date”类型的对象不是JSON可序列化的

What is wrong with my code, and how to structure the output as a DataFrame?

我的代码有什么问题,以及如何将输出结构化为DataFrame?

[update] That's my get_report function:

[更新]那是我的get_report函数:

def get_report(analytics, start_date, end_date, view_id, metrics, dimensions, dimensionFilterClauses):
  return analytics.reports().batchGet(
      body={
        "reportRequests":[
        {
                "viewId": view_id,
                "dateRanges":[{"startDate":start_date,"endDate":end_date}],
                "metrics":metrics,
                "dimensions": dimensions,
                "dimensionFilterClauses": dimensionFilterClauses,
        }]
      }).execute()

1 个解决方案

#1

Have you tried following the quick start

您是否尝试过快速启动

def print_response(response):
  """Parses and prints the Analytics Reporting API V4 response.

  Args:
    response: An Analytics Reporting API V4 response.
  """
  for report in response.get('reports', []):
    columnHeader = report.get('columnHeader', {})
    dimensionHeaders = columnHeader.get('dimensions', [])
    metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])

    for row in report.get('data', {}).get('rows', []):
      dimensions = row.get('dimensions', [])
      dateRangeValues = row.get('metrics', [])

      for header, dimension in zip(dimensionHeaders, dimensions):
        print header + ': ' + dimension

      for i, values in enumerate(dateRangeValues):
        print 'Date range: ' + str(i)
        for metricHeader, value in zip(metricHeaders, values.get('values')):
          print metricHeader.get('name') + ': ' + value