53  

NOTE: pd.convert_objects has now been deprecated. You should use pd.Series.astype(float) or pd.to_numeric as described in other answers.

注意：pd.convert_objects现已弃用。您应该使用pd.Series.astype（float）或pd.to_numeric，如其他答案中所述。

This is available in 0.11. Forces conversion (or set's to nan) This will work even when astype will fail; its also series by series so it won't convert say a complete string column

这是0.11。强制转换（或设置为nan）即使astype失败也会有效;它也是系列的系列所以它不会转换说完整的字符串列

In [10]: df = DataFrame(dict(A = Series(['1.0','1']), B = Series(['1.0','foo'])))

In [11]: df
Out[11]: 
     A    B
0  1.0  1.0
1    1  foo

In [12]: df.dtypes
Out[12]: 
A    object
B    object
dtype: object

In [13]: df.convert_objects(convert_numeric=True)
Out[13]: 
   A   B
0  1   1
1  1 NaN

In [14]: df.convert_objects(convert_numeric=True).dtypes
Out[14]: 
A    float64
B    float64
dtype: object

37  

You can try df.column_name = df.column_name.astype(float). As for the NaN values, you need to specify how they should be converted, but you can use the .fillna method to do it.

您可以尝试df.column_name = df.column_name.astype（float）。至于NaN值，您需要指定它们的转换方式，但您可以使用.fillna方法来完成它。

Example:

例：

In [12]: df
Out[12]: 
     a    b
0  0.1  0.2
1  NaN  0.3
2  0.4  0.5

In [13]: df.a.values
Out[13]: array(['0.1', nan, '0.4'], dtype=object)

In [14]: df.a = df.a.astype(float).fillna(0.0)

In [15]: df
Out[15]: 
     a    b
0  0.1  0.2
1  0.0  0.3
2  0.4  0.5

In [16]: df.a.values
Out[16]: array([ 0.1,  0. ,  0.4])

31  

In a newer version of pandas (0.17 and up), you can use to_numeric function. It allows you to convert the whole dataframe or just individual columns. It also gives you an ability to select how to treat stuff that can't be converted to numeric values:

在较新版本的pandas（0.17及更高版本）中，您可以使用to_numeric函数。它允许您转换整个数据帧或仅转换单个列。它还使您能够选择如何处理无法转换为数值的内容：

import pandas as pd
s = pd.Series(['1.0', '2', -3])
pd.to_numeric(s)
s = pd.Series(['apple', '1.0', '2', -3])
pd.to_numeric(s, errors='ignore')
pd.to_numeric(s, errors='coerce')

20  

df['MyColumnName'] = df['MyColumnName'].astype('float64')