我有一个Dataframe,它的列值如下所示:
[
{
"OrderID" : "0",
"TimeStamp" : "2019-09-24 10:17:48 +0000",
"Screen" : "Home_Screen",
"StateVars" : "",
"Event" : "A"
},
{
"Event" : "B",
"TimeStamp" : "2019-09-24 10:17:38 +0000",
"Screen" : "Home_Screen",
"StateVars" : "",
"OrderID" : "0"
},
{
"OrderID" : "0",
"TimeStamp" : "2019-09-24 10:17:35 +0000",
"Screen" : "Home_Screen",
"StateVars" : "",
"Event" : "D"
},
{
"Event" : "V",
"TimeStamp" : "2019-09-24 10:17:33 +0000",
"Screen" : "Home_Screen",
"StateVars" : "",
"OrderID" : "0"
},
{
"OrderID" : "0",
"TimeStamp" : "2019-09-24 10:17:32 +0000",
"Screen" : "Home_Screen",
"StateVars" : "",
"Event" : "C"
}
]
我要把所有的键列起来。 因此,原始数据帧如下所示:
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+------+------+------+------+-----+
| | O | v | S | I | EventLog | CustomerID | a | b | c | d | e | f |
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+------+------+------+------+-----+
| 0 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | NaN | NaN | NaN | NaN | NaN | NaN |
| 1 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | NaN | NaN | NaN | NaN | NaN | NaN |
| 2 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | NaN | NaN | NaN | NaN | NaN | NaN |
| 3 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | NaN | NaN | NaN | NaN | NaN | NaN |
| 4 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 15 | NaN | NaN | NaN | NaN | NaN | NaN |
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+------+------+------+------+-----+
我在找这样的东西
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+----------------------------+--------------+------------+------+
| | O | v | S | I | EventLog | CustomerID |OrdeID| TimeStamp |Screen | StarsVar |Event |
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+----------------------------+--------------+------------+------+
| 0 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | 0 | 2019-09-24 10:17:33 +0000 | Home_Screen | NaN | A |
| 1 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | 0 | 2019-09-24 10:17:33 +0000 | Home_Screen | NaN | B |
| 2 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | 0 | 2019-09-24 10:17:33 +0000 | Home_Screen | NaN | C |
| 3 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | 0 | 2019-09-24 10:17:33 +0000 | Home_Screen | NaN | D |
| 4 | 1 | 0.4 | OS | 92D42D7E-68F0-4688-83C5-781920E05335 | [{'OrderID': '0', 'TimeStamp': '2019-09-24 10:... | 1 | 0 | 2019-09-24 10:17:33 +0000 | Home_Screen | NaN | E |
+----+------------+-------------+---------+---------------------------------------+----------------------------------------------------+-------------+------+----------------------------+--------------+------------+------+
不必像上面的输出那样删除列。你知道吗
首先由构造函数创建
DataFrame
:对于添加到原件:
编辑:我认为有一些缺少的值,所以解决方法是将它们替换为空dict-最后创建缺少的值:
另一种解决方案:
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