在Python Flask中将Pandas数据帧返回为JSONP响应 [英] Return Pandas dataframe as JSONP response in Python Flask

问题描述

我想返回数据作为Flask中的JSONP响应.

I want to return data as JSONPresponse in Flask.

数据来自Pandas dataframe，我可以使用以下行将其作为JSON返回:

The data comes from a Pandas dataframe and I can return it as JSON with the following line:

json_data = dataframe.to_json(orient='values')
return json_data

工作正常，我得到了数据，看起来像这样:

Works fine and I get the data, which looks like this:

[[1487310600000,1038,1042,1038,1038，-2.243,6.8933]，[1487310900000,1042,1042,1038,1038，-1.3626,4.3058]，[1487311200000,1042,1042,1038,1038，- 1.4631,17.8684]]

[[1487310600000,1038,1042,1038,1038,-2.243,6.8933],[1487310900000,1042,1042,1038,1038,-1.3626,4.3058],[1487311200000,1042,1042,1038,1038,-1.4631,17.8684]]

但是我需要它作为JSONP，所以我使用以下代码:

But I need it as JSONP, so I use the following code:

from flask_jsonpify import jsonpify
json_data = dataframe.to_json(orient='values')
return jsonpify(json_data)

它给了我数据，但带双引号:

And it gives me the data, but with double quotes:

"[[[1487310600000,1038,1042,1038,1038，-2.243,6.8933]，[1487310900000,1042,1042,1038,1038，-1.3626,4.3058]，[1487311200000,1042,1042,1038,1038， -1.4631,17.8684]]"

"[[1487310600000,1038,1042,1038,1038,-2.243,6.8933],[1487310900000,1042,1042,1038,1038,-1.3626,4.3058],[1487311200000,1042,1042,1038,1038,-1.4631,17.8684]]"

如何在Flask中不带双引号的情况下得到JSONP响应? 预先非常感谢.

How can I get the JSONP response in Flask without double quotes? Many thanks in advance.

推荐答案

这是将熊猫数据框转换为JSONP并在Flask中返回的解决方案:

This is my solution to convert a Pandas dataframe to JSONP an return it in Flask:

from flask_jsonpify import jsonpify
df_list = df.values.tolist()
JSONP_data = jsonpify(df_list)
return JSONP_data

根据您需要如何转换数据框，您可能需要以与我不同的方式制作列表，例如像这样的df_list = merged.values.T.tolist()或这样的df_list = list(df.values.flatten())等.

Depending on how you need the dataframe converted, you might need to make the list in a different way as me, e.g. like this df_list = merged.values.T.tolist() or like this df_list = list(df.values.flatten()) etc.

感谢用户@Barmer

Thanks goes to the user @Barmer

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