保存 pandas 数据框以分隔不带NaN的json [英] Saving a pandas dataframe to separate jsons without NaNs

问题描述

我有一个带有某些NaN值的数据框.

I have a dataframe with some NaN values.

这是一个示例数据框:

sample_df = pd.DataFrame([[1,np.nan,1],[2,2,np.nan], [np.nan, 3, 3], [4,4,4],[np.nan,np.nan,5], [6,np.nan,np.nan]])

它看起来像:

获取json之后我做了什么:

What I did after to get a json:

sample_df.to_json(orient = 'records')

哪个给:

'[{"0":1.0,"1":null,"2":1.0},{"0":2.0,"1":2.0,"2":null},{"0":null,"1":3.0,"2":3.0},{"0":4.0,"1":4.0,"2":4.0},{"0":null,"1":null,"2":5.0},{"0":6.0,"1":null,"2":null}]'

我想将此数据帧保存到一个json中，每个json中有2行，但没有Nan值.这是我尝试执行的操作:

I want to save this dataframe to a json with 2 rows in each json, but with none of the Nan values. Here is how I tried to do it:

df_dict = dict((n, sample_df.iloc[n:n+2, :]) for n in range(0, len(sample_df), 2))

for k, v in df_dict.items():
    print(k)
    print(v)
    for d in (v.to_dict('record')):
        for k,v in list(d.items()):
            if type(v)==float:
                if math.isnan(v):
                    del d[k]

json.dumps(df_dict)

我想要的输出:

'[{"0":1.0，"2":1.0}，{"0":2.0，"1":2.0}]'->在一个.json文件中 '.[{"1":3.0，"2":3.0}，{"0":4.0，"1":4.0，"2":4.0}]'->在第二个.json文件中 '.[{"2":5.0}，{"0":6.0}]'->在第三个.json文件中

'[{"0":1.0,"2":1.0},{"0":2.0,"1":2.0}]' -> in one .json file '[{"1":3.0,"2":3.0},{"0":4.0,"1":4.0,"2":4.0}]' -> in second .json file '[{"2":5.0},{"0":6.0}]' -> in third .json file

推荐答案

使用apply删除NaN s，groupby进行分组，并dfGroupBy.apply进行JSONify.

Use apply to drop NaNs, groupby to group and dfGroupBy.apply to JSONify.

s = sample_df.apply(lambda x: x.dropna().to_dict(), 1)\
        .groupby(sample_df.index // 2)\
        .apply(lambda x: x.to_json(orient='records'))
s    

0            [{"0":1.0,"2":1.0},{"0":2.0,"1":2.0}]
1    [{"1":3.0,"2":3.0},{"0":4.0,"1":4.0,"2":4.0}]
2                            [{"2":5.0},{"0":6.0}]
dtype: object

---

最后，遍历.values并保存到单独的JSON文件中.

---

Finally, iterate over .values and save to separate JSON files.

import json
for i, j_data in enumerate(s.values):
    json.dump(j_data, open('File{}.json'.format(i + 1), 'w'))

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