我有一个JSON文件，我想转换为CSV文件。我如何用Python做到这一点?
我试着:
import json
import csv
f = open('data.json')
data = json.load(f)
f.close()
f = open('data.csv')
csv_file = csv.writer(f)
for item in data:
csv_file.writerow(item)
f.close()
然而，这并没有起作用。我正在使用Django和我收到的错误是:
`file' object has no attribute 'writerow'`
然后我尝试了以下方法:
import json
import csv
f = open('data.json')
data = json.load(f)
f.close()
f = open('data.csv')
csv_file = csv.writer(f)
for item in data:
f.writerow(item) # ← changed
f.close()
然后得到错误:
`sequence expected`
样本json文件:
[{
"pk": 22,
"model": "auth.permission",
"fields": {
"codename": "add_logentry",
"name": "Can add log entry",
"content_type": 8
}
}, {
"pk": 23,
"model": "auth.permission",
"fields": {
"codename": "change_logentry",
"name": "Can change log entry",
"content_type": 8
}
}, {
"pk": 24,
"model": "auth.permission",
"fields": {
"codename": "delete_logentry",
"name": "Can delete log entry",
"content_type": 8
}
}, {
"pk": 4,
"model": "auth.permission",
"fields": {
"codename": "add_group",
"name": "Can add group",
"content_type": 2
}
}, {
"pk": 10,
"model": "auth.permission",
"fields": {
"codename": "add_message",
"name": "Can add message",
"content_type": 4
}
}
]
我已经尝试了很多建议的解决方案(也熊猫没有正确地规范化我的JSON)，但真正好的是正确解析JSON数据来自Max Berman。
我写了一个改进，以避免每一行都有新列
在解析期间将其放置到现有列。
如果只有一个数据存在，则将值存储为字符串，如果该列有更多值，则将值存储为列表。
它有一个输入。Json文件作为输入，并输出一个output.csv。
import json
import pandas as pd
def flatten_json(json):
def process_value(keys, value, flattened):
if isinstance(value, dict):
for key in value.keys():
process_value(keys + [key], value[key], flattened)
elif isinstance(value, list):
for idx, v in enumerate(value):
process_value(keys, v, flattened)
# process_value(keys + [str(idx)], v, flattened)
else:
key1 = '__'.join(keys)
if not flattened.get(key1) is None:
if isinstance(flattened[key1], list):
flattened[key1] = flattened[key1] + [value]
else:
flattened[key1] = [flattened[key1]] + [value]
else:
flattened[key1] = value
flattened = {}
for key in json.keys():
k = key
# print("Key: " + k)
process_value([key], json[key], flattened)
return flattened
try:
f = open("input.json", "r")
except:
pass
y = json.loads(f.read())
flat = flatten_json(y)
text = json.dumps(flat)
df = pd.read_json(text)
df.to_csv('output.csv', index=False, encoding='utf-8')
这工作得相对较好。
它将json压缩成csv文件。
嵌套元素被管理:)
这是python 3的
import json
o = json.loads('your json string') # Be careful, o must be a list, each of its objects will make a line of the csv.
def flatten(o, k='/'):
global l, c_line
if isinstance(o, dict):
for key, value in o.items():
flatten(value, k + '/' + key)
elif isinstance(o, list):
for ov in o:
flatten(ov, '')
elif isinstance(o, str):
o = o.replace('\r',' ').replace('\n',' ').replace(';', ',')
if not k in l:
l[k]={}
l[k][c_line]=o
def render_csv(l):
ftime = True
for i in range(100): #len(l[list(l.keys())[0]])
for k in l:
if ftime :
print('%s;' % k, end='')
continue
v = l[k]
try:
print('%s;' % v[i], end='')
except:
print(';', end='')
print()
ftime = False
i = 0
def json_to_csv(object_list):
global l, c_line
l = {}
c_line = 0
for ov in object_list : # Assumes json is a list of objects
flatten(ov)
c_line += 1
render_csv(l)
json_to_csv(o)
享受。
