如何从Pandas数据框中创建JSON,其中列是关键 [英] How to create a json from pandas data frame where columns are the key
问题描述
我有一个数据框df
df:
col1 col2 col3
1 2 3
4 5 6
7 8 9
我正在寻找的json是:
The json I am looking for is:
{
"col1": 1,
"col1": 4,
"col1": 7,
},
{
"col2": 2,
"col2": 5,
"col2": 8
},
{
"col3": 3,
"col3": 6,
"col3": 9,
}
我尝试了df.to_json但它不起作用
I have tries df.to_json but its not working
df.to_json(orients=records)
it gives this output
'[{"col1":1,"col2":2,"col3":3},{"col1":4,"col2":5,"col3":6},
{"col1":7,"col2":8,"col3":9}]
这不是我一直在寻找的输出
This is not the output i was looking for
如何最有效地做到这一点方式使用pandas / python?
How to do it in most effective way using pandas/python ?
推荐答案
JSON文件在python中被视为字典,您指定的JSON文件具有重复的键,并且只能解析为字符串(并且不能使用python json库)。
以下代码:
JSON files are treated as dicts in python, the JSON file you specified has duplicate keys and could only be parsed as a string (and not using the python json library). The following code:
import json
from io import StringIO
df = pd.DataFrame(np.arange(1,10).reshape((3,3)), columns=['col1','col2','col3'])
io = StringIO()
df.to_json(io, orient='columns')
parsed = json.loads(io.getvalue())
with open("pretty.json", '+w') as of:
json.dump(parsed, of, indent=4)
会产生以下JSON:
{
"col1": {
"0": 1,
"1": 4,
"2": 7
},
"col2": {
"0": 2,
"1": 5,
"2": 8
},
"col3": {
"0": 3,
"1": 6,
"2": 9
}
}
您可以稍后将其加载到python中。或者,此脚本将完全生成您想要的字符串:
which you could later load to python. alternatively, this script will produce exatcly the string you want:
with open("exact.json", "w+") as of:
of.write('[\n\t{\n' + '\t},\n\t{\n'.join(["".join(["\t\t\"%s\": %s,\n"%(c, df[c][i]) for i in df.index]) for c in df.columns])+'\t}\n]')
,输出为:
[
{
"col1": 1,
"col1": 4,
"col1": 7,
},
{
"col2": 2,
"col2": 5,
"col2": 8,
},
{
"col3": 3,
"col3": 6,
"col3": 9,
}
]
编辑:固定括号
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