Python 将对象转换为浮点数

Python convert object to float

提问by Almog Woldenberg

I read some weather data from a csv file as a dataframe named "weather". The problem is that one of the columns' data type is an object. this is weird beacuse it indicates temperature... anyway, how to I change it to a float? I tried to_numeric but it can't parse it.

我从一个 csv 文件中读取了一些天气数据作为名为“weather”的数据框。问题是列的数据类型之一是对象。这很奇怪，因为它表示温度……无论如何，我如何将其更改为浮点数？我试过 to_numeric 但它无法解析它。

weather.info()
weather.head()

<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 304 entries, 2017-01-01 to 2017-10-31
Data columns (total 2 columns):
Temp    304 non-null object
Rain    304 non-null float64
dtypes: float64(1), object(1)
memory usage: 17.1+ KB

           Temp     Rain
Date        
2017-01-01  12.4    0.0
2017-02-01  11      0.6
2017-03-01  10.4    0.6
2017-04-01  10.9    0.2
2017-05-01  13.2    0.0

回答by Jai

• You can use pandas.Series.astype

• You can do something like this :

  weather["Temp"] = weather.Temp.astype(float)
  

• You can also use pd.to_numericthat will convert the column from object to float

• For details on how to use it checkout this link :http://pandas.pydata.org/pandas-docs/version/0.20/generated/pandas.to_numeric.html

• Example :

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

• Output:

  0    apple
  1      1.0
  2        2
  3       -3
  =========================
  dtype: object
  0    NaN
  1    1.0
  2    2.0
  3   -3.0
  dtype: float64
  

• In your case you can do something like this:

  weather["Temp"] = pd.to_numeric(weather.Temp, errors='coerce')
  

• Other option is to use convert_objects

• Example is as follows

  >> pd.Series([1,2,3,4,'.']).convert_objects(convert_numeric=True)
  
  0     1
  1     2
  2     3
  3     4
  4   NaN
  dtype: float64
  

• You can use this as follows:

  weather["Temp"] = weather.Temp.convert_objects(convert_numeric=True)
  

• I have showed you examples because if any of your column won't have a number then it will be converted to NaN... so be careful while using it

• ENJOY !!!!!!!!!!!!!! :)

• 您可以使用 pandas.Series.astype

• 你可以这样做：

  weather["Temp"] = weather.Temp.astype(float)
  

• 您还可以使用pd.to_numeric它将列从对象转换为浮动

• 有关如何使用它的详细信息，请查看此链接：http: //pandas.pydata.org/pandas-docs/version/0.20/generated/pandas.to_numeric.html

• 例子 ：

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

• 输出：

  0    apple
  1      1.0
  2        2
  3       -3
  =========================
  dtype: object
  0    NaN
  1    1.0
  2    2.0
  3   -3.0
  dtype: float64
  

• 在您的情况下，您可以执行以下操作：

  weather["Temp"] = pd.to_numeric(weather.Temp, errors='coerce')
  

• 其他选择是使用 convert_objects

• 例子如下

  >> pd.Series([1,2,3,4,'.']).convert_objects(convert_numeric=True)
  
  0     1
  1     2
  2     3
  3     4
  4   NaN
  dtype: float64
  

• 您可以按如下方式使用它：

  weather["Temp"] = weather.Temp.convert_objects(convert_numeric=True)
  

• 我已经向您展示了示例，因为如果您的任何列没有数字，那么它将被转换为NaN......所以在使用它时要小心

• 请享用 ！！！！！！！！！！！！！！:)

回答by Almog Woldenberg

I eventually used:

我最终使用了：

weather["Temp"] = weather["Temp"].convert_objects(convert_numeric=True)

It worked just fine, except that I got the following message.

它工作得很好，除了我收到以下消息。

C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:3: FutureWarning:
convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.