将Bigquery结果转换为Pandas数据框 [英] Convert Bigquery results to Pandas Data Frame

问题描述

下面是将BigQuery结果转换为Pandas数据框的代码.我正在学习Python&Pandas，想知道我是否可以就代码的任何改进获得建议/想法?

Below is the code to convert BigQuery results into Pandas data frame. Im learning Python&Pandas and wonder if i can get suggestion/ideas about any kind of improvements to the code?

#...code to run query, that returns 3 columns: 'date' DATE, 'currency' STRING,'rate' FLOAT...

rows, total_count, token = query.fetch_data()
currency = []
rate = []
dates = []
for row in rows:
    dates.append(row[0])
    currency.append(row[1])
    rate.append(row[2])


dict = {
'currency' : currency,
'date' : dates,
'rate' : rate
}

df2 = pd.DataFrame(dict)

df2['date'] = pd.to_datetime(df2['date'])
df2 = df2.set_index('date')

上面的作品.但是看起来很矮胖.有什么方法可以比上述方法更有效地做同样的事情?我尝试了诸如sqlalchemy之类的库，但它们不支持BigQuery.通常，我的问题是上面的代码和语法.

The above works. But looks chunky. Is there any way to do the same thing more efficiently than the above? I tried libraries such as sqlalchemy but they do not support BigQuery. And generally my question is about code and syntax above.

推荐答案

您应该改用 read_gbq(): https://pandas.pydata.org/pandas-docs/stable/generation/pandas.read_gbq.html

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