使用pandas将string对象转换为int/float
使用pandas将string对象转换为int/float
提问于 2014-06-04 20:31:34
import pandas as pd
path1 = "/home/supertramp/Desktop/100&life_180_data.csv"
mydf = pd.read_csv(path1)
numcigar = {"Never":0 ,"1-5 Cigarettes/day" :1,"10-20 Cigarettes/day":4}
print mydf['Cigarettes']
mydf['CigarNum'] = mydf['Cigarettes'].apply(numcigar.get).astype(float)
print mydf['CigarNum']
mydf.to_csv('/home/supertramp/Desktop/powerRangers.csv')csv文件"100&life_180_data.csv“包含诸如年龄、体重指数、香烟、酒精等列。
No int64
Age int64
BMI float64
Alcohol object
Cigarettes object
dtype: object香烟列包含“从不”、"1-5支/天“、"10-20支/天”。我想为这些对象分配权重(从不，1-5支/天，....)
预期的输出是附加的新列CigarNum，它只包含数字0,1,2 CigarNum如预期的那样直到8行，然后在CigarNum列中显示Nan到最后一行
0 Never
1 Never
2 1-5 Cigarettes/day
3 Never
4 Never
5 Never
6 Never
7 Never
8 Never
9 Never
10 Never
11 Never
12 10-20 Cigarettes/day
13 1-5 Cigarettes/day
14 Never
...
167 Never
168 Never
169 10-20 Cigarettes/day
170 Never
171 Never
172 Never
173 Never
174 Never
175 Never
176 Never
177 Never
178 Never
179 Never
180 Never
181 Never
Name: Cigarettes, Length: 182, dtype: object我得到的输出不应该在前几行之后给出NaN。
0 0
1 0
2 1
3 0
4 0
5 0
6 0
7 0
8 0
9 0
10 NaN
11 NaN
12 NaN
13 NaN
14 0
...
167 NaN
168 NaN
169 NaN
170 NaN
171 NaN
172 NaN
173 NaN
174 NaN
175 NaN
176 NaN
177 NaN
178 NaN
179 NaN
180 NaN
181 NaN
Name: CigarNum, Length: 182, dtype: float64回答 1
Stack Overflow用户
发布于 2015-05-15 04:17:06
尝试使用此函数来解决所有此类问题：
def get_series_ids(x):
'''Function returns a pandas series consisting of ids,
corresponding to objects in input pandas series x
Example:
get_series_ids(pd.Series(['a','a','b','b','c']))
returns Series([0,0,1,1,2], dtype=int)'''
values = np.unique(x)
values2nums = dict(zip(values,range(len(values))))
return x.replace(values2nums)页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/24037507
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