Question

我正在逐行读取文件并处理每一行。但是我没有得到所需的输出。

inputfile.txt

{"M":{"1":"data","2":"esf"},"D":{"4":12312,"6":"err"},"R":{"33":"eres","wer":454}}
{"M":{"1":"a","2":"2"},"D":{"4":3456,"6":"esrr"},"R":{"33":"esre","wer":447}}
{"M":{"1":"data3","2":"fer"},"D":{"4":9873,"6":"errs"},"R":{"33":"eret","wer":189,"55":"rt"}}

代码：

import pandas as pd;
import json
with open("inputfile.txt") as f:
  for line in f:
    data=(json.loads(f))
    d=[{k1+k2:v2 for k2,v2 in v1.items()} for k1,v1 in data.items()]
    keys=[k for x in d for k in x.items()]
    keys=list(set(keys))
    df=pd.DataFrame(d,columns=keys)
    print (df)

我需要的输出：

M1,M2,D4,D6,R33,Rwer,R55
data,esf,12312,err,eres,454,NA
a,2,3456,esrr,esre,447,NA
data3,fer,9873,errs,eret,189,rt

Answer 1

尝试

with open("inputfile.txt") as f:
    for line in f:
        proccess_lines(json.loads(line))

Answer 2

您必须读取一次文件，并将每一行作为Json字符串加载，然后再进行处理。代码可能是：

df = pd.DataFrame([{k1+k2:v2 for k1,v1 in data.items() for k2,v2 in v1.items()} 
                   for data in [json.loads(line) for line in io.StringIO(t)]])

这将构建一个列表理解，每行包含一个字典，最后从中构建一个数据框。

有了您的样本数据，我得到：

      D4    D6     M1   M2   R33  R55  Rwer
0  12312   err   data  esf  eres  NaN   454
1   3456  esrr      a    2  esre  NaN   447
2   9873  errs  data3  fer  eret   rt   189

如果要重新排列列，只需使用：

df[['M1', 'M2', 'D4', 'D6', 'R33', 'Rwer', 'R55']]

给予预期：

      M1   M2     D4    D6   R33  Rwer  R55
0   data  esf  12312   err  eres   454  NaN
1      a    2   3456  esrr  esre   447  NaN
2  data3  fer   9873  errs  eret   189   rt

Answer 3

使用中间文本I / O缓冲区（还充当上下文管理器）的扩展解决方案：

import pandas as pd
import json
import io

with open('input.json') as f, io.StringIO() as temp_file:
    for line in f:
        d = {}
        json_data = json.loads(line)
        d = {k + sub_k: val for k, inner_d in json_data.items()
             for sub_k, val in inner_d.items()}
        temp_file.write(json.dumps(d) + '\n')
    temp_file.seek(0)

    df = pd.read_json(temp_file, orient='columns', lines=True)
    print(df.to_string())

示例输出：

      D4    D6     M1   M2   R33  R55  Rwer
0  12312   err   data  esf  eres  NaN   454
1   3456  esrr      a    2  esre  NaN   447
2   9873  errs  data3  fer  eret   rt   189

逐行读取大型json（> 5gb）文件并处理每一行并使用Pandas创建DataFrame

3 个答案: