从Pandas数据框中的行填充字典

Question

我想用数据框架中包含的值填充大量字典。理想情况下，每行应该用来填充一个字典，该字典将被附加到一个字典列表中。

#example df
firstname | lastname | dob        | modified   | created
john        smith      1990-01-01   2019-10-11   2015-06-25
becca       meyers     1995-04-13   2020-01-08   2018-05-18

每个字典看起来应该是这样的:(请忽略这个事实，在这个例子中这是没有意义的，这就是必须要做的)

d = {
  "firstname" : {
      "value": df['firstname'],
      "modified": df['modified'],
      "created": df['created']
   },{
   "lastname": {
     "value": df['lastname'],
     "modified": df['modified'],
     "created": df['created']
   }
}

我试过通过df做一个for循环，但它只是在每个字段中填充整个数据帧，这不是我所希望的。

l = []
for x in df:
    d = {
        "firstname" : {
            "value": df['firstname'],
            "modified": df['modified'],
            "created": df['created']
        },{
        "lastname": {
            "value": df['lastname'],
            "modified": df['modified'],
            "created": df['created']
           }
       }
    l.append(d)

ninjaedit:我的预期输出应该是:

l = [{ 
   "firstname": {
   "value": "john",
   "modified": 2019-10-11,
   "created": 2015-06-25}
   },{
   "lastname": {
   "value": "smith",
   "modified": 2019-10-11,
   "created": 2015-06-25}},
   ...
}]

我已经有几个月没有做任何python/pandas了，所以我有点生疏了。提前感谢。如果这让你感到困惑，我很抱歉，如果需要的话，我可以展开。

Answer 1

使用DataFrame.itertuples:

l = []
for x in df.itertuples():
    d = {
        "firstname" : {
            "value": x.firstname,
            "modified": x.modified,
            "created": x.created
        },
        "lastname": {
            "value": x.lastname,
            "modified": x.modified,
            "created": x.created
            }
        }
    l.append(d)
print (l)
[{'firstname': {'value': 'john', 'modified': '2019-10-11', 'created': '2015-06-25'}, 
  'lastname': {'value': 'smith', 'modified': '2019-10-11', 'created': '2015-06-25'}}, 
 {'firstname': {'value': 'becca', 'modified': '2020-01-08', 'created': '2018-05-18'}, 
  'lastname': {'value': 'meyers', 'modified': '2020-01-08', 'created': '2018-05-18'}}]

Slowier选择:

l = []
for i, x in df.iterrows():
    d = {
        "firstname" : {
            "value": x.firstname,
            "modified": x.modified,
            "created": x.created
        },
        "lastname": {
            "value": x.lastname,
            "modified": x.modified,
            "created": x.created
            }
        }
    l.append(d)

Answer 2

你应该在循环中使用div .iterrows()

这里有一篇关于如何迭代pandas dataframe的小文章