Python 熊猫：从dataframe创建json文件

我有数据帧

ID, visiting
111, 03.2015
111, 07.2015
111, 05.2016
222, 12.2013
222, 04.2016
333, 02.2014
333, 06.2015,
333, 11.2015

我需要像这样获取文件（我需要指定从2013年12月到2016年6月的所有月份）

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我怎样才能从熊猫那里得到它呢？

使用

groupby

s会更有效，但这样就完成了任务：

txt = """ID, visiting
111, 03.2015
111, 07.2015
111, 05.2016
222, 12.2013
222, 04.2016
333, 02.2014
333, 06.2015
333, 11.2015"""

split = [line.split(', ') for line in txt.split('\n')]

df = pd.DataFrame(split[1:], columns=split[0])

results = {}
for ID in df.ID.unique():
    results[ID] = {}

for year in range(2013, 2017):
    if year == 2013:
        months = [12]
    elif year == 2016:
        months = range(1, 7)
    else:
        months = range(1, 13)
    for month in months:
        search_text = '{:02d}.{}'.format(month, year)
        result_text = '{}-{:02d}'.format(year, month)
        for ID in df.ID.unique():
            if len(df[(df.ID == ID)&(df.visiting == search_text)]) > 0:
                boolean = 1
            else:
                boolean = 0
            results[ID][result_text] = boolean

import json
results = json.dumps(results)

txt = """ID, visiting
111, 03.2015
111, 07.2015
111, 05.2016
222, 12.2013
222, 04.2016
333, 02.2014
333, 06.2015
333, 11.2015"""

split = [line.split(', ') for line in txt.split('\n')]

df = pd.DataFrame(split[1:], columns=split[0])

results = {}
for ID in df.ID.unique():
    results[ID] = {}

for year in range(2013, 2017):
    if year == 2013:
        months = [12]
    elif year == 2016:
        months = range(1, 7)
    else:
        months = range(1, 13)
    for month in months:
        search_text = '{:02d}.{}'.format(month, year)
        result_text = '{}-{:02d}'.format(year, month)
        for ID in df.ID.unique():
            if len(df[(df.ID == ID)&(df.visiting == search_text)]) > 0:
                boolean = 1
            else:
                boolean = 0
            results[ID][result_text] = boolean

import json
results = json.dumps(results)