Python：如何从 pandas 系列的字典获取值 [英] Python: how to get values from a dictionary from pandas series

问题描述

我对python非常新鲜，并试图从数据框（pandas）中定义键的字典获取值。我搜索了很多，最接近的是一个
问题在下面的链接，但它没有一个答案。

I am very new to python and trying to get value from dictionary where keys are defined in a dataframe column (pandas). I searched quite a bit and the closest thing is a question in the link below, but it doesnt come with an answer.

所以，在这里我试图找到同样类型的问题的答案。

So, here I am trying to find answer for the same type of question.

从使用大熊猫的字典中选择系列

我有一个字典

type_dict = {3: 'foo', 4:'bar',5:'foobar', 6:'foobarbar'}

和具有以下列的数据框：

and a data frame with the following column:

>>> df.type
0     3
1     4
2     5
3     6
4     3
5     4
6     5
7     6
8     3

我想创建一个包含相应的type_dict值的新列，但是以下是我唯一可以提出并且不起作用的：

I want to create a new column containing the corresponding type_dict value, but the following was the only thing I could come up and was not working:

type_dict[df.type]

TypeError：'Series'对象是可变的，因此它们不能被哈希

TypeError: 'Series' objects are mutable, thus they cannot be hashed

type_dict[df.type.values]

TypeError ：unhashable类型：'numpy.ndarray'

TypeError: unhashable type: 'numpy.ndarray'

更新问题：

为大熊猫DataFrame，说'df' ，我如何绘制速度超过米的类型作为标记字典的关键。

for pandas DataFrame, say 'df', how can i plot speed over meters with type as the key of marker dictionary.

mkr_dict = {'gps': 'x', 'phone': '+', 'car': 'o'}

x = {'speed': [10, 15, 20, 18, 19], 'meters' : [122, 150, 190, 230, 300], 'type': ['phone', 'phone', 'gps', 'gps', 'car']}

df = pd.DataFrame(x)
   meters  speed   type
0     122     10  phone
1     150     15  phone
2     190     20    gps
3     230     18    gps
4     300     19    car

plt.scatter(df.meters, df.Speed, marker = df.type.map(mkr_dict)) 

散点图不适合我...

the scatter plot doesn't work for me...

推荐答案

将dict作为参数传递给 map ：

Pass the dict as an arg to map:

In [79]:

df['type'].map(type_dict)
Out[79]:
0          foo
1          bar
2       foobar
3    foobarbar
4          foo
5          bar
6       foobar
7    foobarbar
8          foo
Name: type, dtype: object

这将查找口头和回报t他与dict相关联的价值。

This will lookup the key value in the dict and return the associated value from the dict.

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