我是Python新手,对于我的一个项目,我需要将csv转换为嵌套Json。在网上搜索时,我发现pandas
在这种情况下很有用。
我遵循了Convert CSV Data to Nested JSON in Python中给出的建议
但是我得到了一个keyError异常KeyError: 'state'
df info
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4 entries, 0 to 3
Data columns (total 3 columns):
country 4 non-null object
state 4 non-null object
city 4 non-null object
dtypes: object(3)
memory usage: 176.0+ bytes
None
Traceback (most recent call last):
File "csvToJson.py", line 31, in <module>
grouped = df.groupby(['country', 'state'])
File "/home/simarpreet/Envs/j/lib/python3.7/site-packages/pandas/core/generic.py", line 7632, in groupby
observed=observed, **kwargs)
File "/home/simarpreet/Envs/j/lib/python3.7/site-packages/pandas/core/groupby/groupby.py", line 2110, in groupby
return klass(obj, by, **kwds)
File "/home/simarpreet/Envs/j/lib/python3.7/site-packages/pandas/core/groupby/groupby.py", line 360, in __init__
mutated=self.mutated)
File "/home/simarpreet/Envs/j/lib/python3.7/site-packages/pandas/core/groupby/grouper.py", line 578, in _get_grouper
raise KeyError(gpr)
KeyError: 'state'
输入csv:
^{pr2}$我的代码:
csvFilePath = "/home/simarpreet/sampleCsv.csv"
jsonFilePath = "/home/simarpreet/sampleJson.json"
jsonFile = open(jsonFilePath, 'w')
df = pd.read_csv(csvFilePath, encoding='utf-8-sig')
print("df info")
print(df.info())
finalList = []
grouped = df.groupby(['country', 'state'])
for key, value in grouped:
dictionary = {}
j = grouped.get_group(key).reset_index(drop=True)
dictionary['country'] = j.at[0, 'country']
dictionary['state'] = j.at[0, 'state']
dictList = []
anotherDict = {}
for i in j.index:
anotherDict['city'] = j.at[i, 'city']
dictList.append(anotherDict)
dictionary['children'] = dictList
finalList.append(dictionary)
json.dumps(finalList)
问题是你的csv文件,列名中有前导whitespaces,因此键错误就来了。在
正如@cs95所指出的,你可以做到
也可以使用read_csv处理空间:
pd.read_csv(csvFilePath, encoding='utf-8-sig', sep='\s*,\s*', engine='python')
PS:糟糕的处理方法:
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