我正在尝试使用solution将dataFrame导出到D3.js的嵌套JSON（分层）JSON中（仅适用于一个级别（父级，子级）
）任何帮助将不胜感激。我是python的新手
我的DataFrame包含7个级别 这是预期的解决方案
JSON Example:
{
"name": "World",
"children": [
{
"name": "Europe",
"children": [
{
"name": "France",
"children": [
{
"name": "Paris",
"population": 1000000
}]
}]
}]
}
这是python方法：
def to_flare_json(df, filename):
"""Convert dataframe into nested JSON as in flare files used for D3.js"""
flare = dict()
d = {"name":"World", "children": []}
for index, row in df.iterrows():
parent = row[0]
child = row[1]
child1 = row[2]
child2 = row[3]
child3 = row[4]
child4 = row[5]
child5 = row[6]
child_value = row[7]
# Make a list of keys
key_list = []
for item in d['children']:
key_list.append(item['name'])
#if 'parent' is NOT a key in flare.JSON, append it
if not parent in key_list:
d['children'].append({"name": parent, "children":[{"value": child_value, "name1": child}]})
# if parent IS a key in flare.json, add a new child to it
else:
d['children'][key_list.index(parent)]['children'].append({"value": child_value, "name11": child})
flare = d
# export the final result to a json file
with open(filename +'.json', 'w') as outfile:
json.dump(flare, outfile, indent=4,ensure_ascii=False)
return ("Done")
[编辑]
这是我的df样本
World Continent Region Country State City Boroughs Population
1 Europe Western Europe France Ile de France Paris 17 821964
1 Europe Western Europe France Ile de France Paris 19 821964
1 Europe Western Europe France Ile de France Paris 20 821964
答案 0 :(得分：0)
您想要的结构显然是递归的，所以我做了一个递归函数来填充它：
enc_out剩下的就是创建字典并调用函数：
def create_entries(df):
entries = []
# Stopping case
if df.shape[1] == 2: # only 2 columns left
for i in range(df.shape[0]): # iterating on rows
entries.append(
{"Name": df.iloc[i, 0],
df.columns[-1]: df.iloc[i, 1]}
)
# Iterating case
else:
values = set(df.iloc[:, 0]) # Getting the set of unique values
for v in values:
entries.append(
{"Name": v,
# reiterating the process but without the first column
# and only the rows with the current value
"Children": create_entries(
df.loc[df.iloc[:, 0] == v].iloc[:, 1:]
)}
)
return entries
然后，您只需将字典写入JSON文件即可。
我希望我的评论足够明确，其想法是递归地将数据集的第一列用作“名称”，其余部分用作“子代”。
答案 1 :(得分：0)
谢谢Syncrossus的回答，但这会导致每个行政区或城市的分支机构不同 结果是这样的：
"Name": "World",
"Children": [
{
"Name": "Western Europe",
"Children": [
{
"Name": "France",
"Children": [
{
"Name": "Ile de France",
"Children": [
{
"Name": "Paris",
"Children": [
{
"Name": "17ème",
"Population": 821964
}
]
}
]
}
]
}
]
},{
"Name": "Western Europe",
"Children": [
{
"Name": "France",
"Children": [
{
"Name": "Ile de France",
"Children": [
{
"Name": "Paris",
"Children": [
{
"Name": "10ème",
"Population": 154623
}
]
}
]
}
]
}
]
}
但是期望的结果是这个
"Name": "World",
"Children": [
{
"Continent": "Europe",
"Children": [
{
"Region": "Western Europe",
"Children": [
{
"Country": "France",
"Children": [
{
"State": "Ile De France",
"Children": [
{
"City": "Paris",
"Children": [
{
"Boroughs": "17ème",
"Population": 82194
},
{
"Boroughs": "16ème",
"Population": 99194
}
]
},
{
"City": "Saint-Denis",
"Children": [
{
"Boroughs": "10ème",
"Population": 1294
},
{
"Boroughs": "11ème",
"Population": 45367
}
]
}
]
}
]
},
{
"Country": "Belgium",
"Children": [
{
"State": "Oost-Vlaanderen",
"Children": [
{
"City": "Gent",
"Children": [
{
"Boroughs": "2ème",
"Population": 1234
},
{
"Boroughs": "4ème",
"Population": 7456
}
]
}
]
}
]
}
]
}
]
}
]