相关疑难解决方法(0)

我是Python和Pandas的新手.我正在尝试将Pandas Dataframe转换为嵌套的JSON.函数.to_json()没有给我足够的灵活性来实现我的目标.

以下是数据帧的一些数据点(以csv,逗号分隔):

,ID,Location,Country,Latitude,Longitude,timestamp,tide  
0,1,BREST,FRA,48.383,-4.495,1807-01-01,6905.0  
1,1,BREST,FRA,48.383,-4.495,1807-02-01,6931.0  
2,1,BREST,FRA,48.383,-4.495,1807-03-01,6896.0  
3,1,BREST,FRA,48.383,-4.495,1807-04-01,6953.0  
4,1,BREST,FRA,48.383,-4.495,1807-05-01,7043.0  
2508,7,CUXHAVEN 2,DEU,53.867,8.717,1843-01-01,7093.0  
2509,7,CUXHAVEN 2,DEU,53.867,8.717,1843-02-01,6688.0  
2510,7,CUXHAVEN 2,DEU,53.867,8.717,1843-03-01,6493.0  
2511,7,CUXHAVEN 2,DEU,53.867,8.717,1843-04-01,6723.0  
2512,7,CUXHAVEN 2,DEU,53.867,8.717,1843-05-01,6533.0  
4525,9,MAASSLUIS,NLD,51.918,4.25,1848-02-01,6880.0  
4526,9,MAASSLUIS,NLD,51.918,4.25,1848-03-01,6700.0  
4527,9,MAASSLUIS,NLD,51.918,4.25,1848-04-01,6775.0  
4528,9,MAASSLUIS,NLD,51.918,4.25,1848-05-01,6580.0  
4529,9,MAASSLUIS,NLD,51.918,4.25,1848-06-01,6685.0  
6540,8,WISMAR 2,DEU,53.898999999999994,11.458,1848-07-01,6957.0  
6541,8,WISMAR 2,DEU,53.898999999999994,11.458,1848-08-01,6944.0  
6542,8,WISMAR 2,DEU,53.898999999999994,11.458,1848-09-01,7084.0  
6543,8,WISMAR 2,DEU,53.898999999999994,11.458,1848-10-01,6898.0  
6544,8,WISMAR 2,DEU,53.898999999999994,11.458,1848-11-01,6859.0  
8538,10,SAN FRANCISCO,USA,37.806999999999995,-122.465,1854-07-01,6909.0  
8539,10,SAN FRANCISCO,USA,37.806999999999995,-122.465,1854-08-01,6940.0  
8540,10,SAN FRANCISCO,USA,37.806999999999995,-122.465,1854-09-01,6961.0  
8541,10,SAN FRANCISCO,USA,37.806999999999995,-122.465,1854-10-01,6952.0  
8542,10,SAN FRANCISCO,USA,37.806999999999995,-122.465,1854-11-01,6952.0  

有很多重复的信息,我想有这样的JSON:

[
{
    "ID": 1,
    "Location": "BREST",
    "Latitude": 48.383,
    "Longitude": -4.495,
    "Country": "FRA",
    "Tide-Data": {
        "1807-02-01": 6931,
        "1807-03-01": 6896,
        "1807-04-01": 6953,
        "1807-05-01": 7043
    }
},
{
    "ID": 5,
    "Location": "HOLYHEAD",
    "Latitude": 53.31399999999999,
    "Longitude": -4.62,
    "Country": "GBR", …

我经常使用pandas groupby来生成堆叠表.但后来我经常想要将生成的嵌套关系输出到json.有没有办法从它生成的堆栈表中提取嵌套的json字段？

假设我有一个像:

year office candidate  amount
2010 mayor  joe smith  100.00
2010 mayor  jay gould   12.00
2010 govnr  pati mara  500.00
2010 govnr  jess rapp   50.00
2010 govnr  jess rapp   30.00

我可以:

grouped = df.groupby('year', 'office', 'candidate').sum()

print grouped
                       amount
year office candidate 
2010 mayor  joe smith   100
            jay gould    12
     govnr  pati mara   500
            jess rapp    80

美丽!当然,我真正喜欢做的是通过沿groups.to_json行的命令获得嵌套的json.但是这个功能不可用.任何解决方法？

所以,我真正想要的是:

{"2010": {"mayor": [
                    {"joe smith": 100},
                    {"jay gould": 12}
                   ]
         }, 
          {"govnr": [
                     {"pati mara":500}, 
                     {"jess rapp": 80}
                    ] …

由于问题解释了问题,我一直在尝试生成嵌套的JSON对象.在这种情况下,我有for循环从字典中获取数据dic.以下是代码:

f = open("test_json.txt", 'w')
flag = False
temp = ""
start = "{\n\t\"filename\"" + " : \"" +initial_filename+"\",\n\t\"data\"" +" : " +" [\n"
end = "\n\t]" +"\n}"
f.write(start)
for i, (key,value) in enumerate(dic.iteritems()):
    f.write("{\n\t\"keyword\":"+"\""+str(key)+"\""+",\n")
    f.write("\"term_freq\":"+str(len(value))+",\n")
    f.write("\"lists\":[\n\t")
    for item in value:
        f.write("{\n")
        f.write("\t\t\"occurance\" :"+str(item)+"\n")
        #Check last object
        if value.index(item)+1 == len(value):
            f.write("}\n" 
            f.write("]\n")
        else:
            f.write("},") # close occurrence object
    # Check last item in dic
    if i == len(dic)-1:
        flag = True
    if(flag):
        f.write("}")
    else:
        f.write("},") …