相关疑难解决方法(0)

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age,bmi,Cigarettes,Alocohol等列.

No                int64
Age               int64
BMI             float64
Alcohol          object
Cigarettes       object
dtype: object

香烟专栏包含"Never""1-5 Cigarettes/day","10-20 Cigarettes/day".我想为这些物体分配重量(从不,1-5根香烟/天,......)

预期的输出是附加的新列CigarNum,其仅包含数字0,1,2 CigarNum如预期的那样直到8行然后显示Nan直到CigarNum列中的最后一行

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 …

我遇到了错误

'str' 和 'int' 实例之间不支持 '>'

尝试在 Pandas 数据框中打印以下行时

print (survey_df_clean.shape)
print (survey_df_clean[survey_df_clean['text']>30].shape)

我应该尝试将它们转换为 int 吗？在这个语句中这将如何工作？

我有一个包含美国国会传记数据的.csv ，我将其作为 Panda df 阅读：

df = pd.read_csv('congress100.csv', delimiter = ';', names = ['Name', 'Position', 'Party', 'State', 'Congress'], header = 0)

我的数据框如下所示：

0                   'ACKERMAN, Gary Leonard'        'Representative'    'Democrat'  'NY'  '100(1987-1988)'
1                  'ADAMS, Brockman (Brock)'               'Senator'    'Democrat'  'WA'  '100(1987-1988)'
2                   'AKAKA, Daniel Kahikina'        'Representative'    'Democrat'  'HI'  '100(1987-1988)'
3    'ALEXANDER, William Vollie (Bill), Jr.'        'Representative'    'Democrat'  'AR'  '100(1987-1988)'
4                  'ANDERSON, Glenn Malcolm'        'Representative'    'Democrat'  'CA'  '100(1987-1988)'
5                   'ANDREWS, Michael Allen'        'Representative'    'Democrat'  'TX'  '100(1987-1988)'
6                          'ANNUNZIO, Frank'        'Representative'    'Democrat'  'IL' …