<p>欢迎光临!这个怎么样,作为解决问题的一种方法。在</p>
<pre><code># import the pandas library so we can use it's from_dict function:
import pandas as pd
# subset the json to a dict of exchange rates and country codes:
d = data['rates']
# create a dataframe from this data, using pandas from_dict function:
df = pd.DataFrame.from_dict(d,orient='index')
# add a column for date (this value is taken from the json data):
df['date'] = data['date']
# name our columns, to keep things clean
df.columns = ['rate','date']
</code></pre>
<p>这将为您提供:</p>
^{pr2}$
<p>在这种情况下,货币是数据帧的索引,如果您希望它作为它自己的列,只需添加:
<code>df['currency'] = df.index</code></p>
<p>然后可以将此数据帧写入.csv文件,或写入BigQuery。在</p>
<p>为此,我建议您看一看<a href="https://cloud.google.com/bigquery/docs/reference/libraries" rel="nofollow noreferrer">The BigQuery Client library</a>,一开始可能有点难理解,所以您可能还想看看<a href="https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_gbq.html" rel="nofollow noreferrer">pandas.DataFrame.to_gbq</a>,它更简单,但不太健壮(有关客户端库与pandas函数的详细信息,请参见<a href="https://cloud.google.com/bigquery/docs/pandas-gbq-migration" rel="nofollow noreferrer">this link</a>)。在</p>