我们有时候在对组数进行操作时候，偶尔会出现这个问题.
比如：
#coding:utf-8 import pandas as pd import numpy as np if __name__ == ‘__main__‘: np.random.seed(0) df = pd.DataFrame(100 + np.random.randn(100).cumsum(), columns=[‘weight‘]) df[‘pct_change‘] = df.weight.pct_change() df[‘w_log‘] = np.log(np.asarray(df[‘weight‘]+2 , dtype=object)) print df[‘w_log‘]
会出现这个问题：
df[‘w_log‘] = np.log(np.asarray(df[‘weight‘]+2 , dtype=object)) AttributeError: ‘float‘ object has no attribute ‘log‘
这个问题的原因是object没有log操作：上述操作等同于
np.log(np.array([x], dtype=object)) <-> np.array([x.log()], dtype=object)
那么我们该怎么样来修正呢？#coding:utf-8 import pandas as pd import numpy as np if __name__ == ‘__main__‘: np.random.seed(0) df = pd.DataFrame(100 + np.random.randn(100).cumsum(), columns=[‘weight‘]) df[‘pct_change‘] = df.weight.pct_change() df[‘w_log‘] = np.log(np.asarray(df[‘weight‘]+2 , dtype=float)) print df[‘w_log‘]
将object对象，改成base类型就可以了.
结果：
0 4.642120 1 4.645969 2 4.655321 3 4.676410 4 4.693652 5 4.684666 6 4.693403 7 4.692016 8 4.691069 9 4.694830 10 4.696146 11 4.709337 12 4.716171
完.
