python-3.x - 显示多个满足特定条件的数据-PANDAS 中的问题

Question

我正在使用 Python 在 PANDAS 中工作，并且正在查看天气 CSV 文件。我可以毫无问题地从中提取数据。但是，我无法提取符合某些标准的数据，例如何时显示哪些天的温度高于 100 度。

到目前为止，我有这个作为我的代码:

import pandas as pd
import numpy as np 
import matplotlib.pyplot as plt 

df = pd.read_csv('csv/weather.csv')

print(df[[df.MaxTemperatureF > 100 ]])

最后一行是我认为我有问题的地方。在执行以下步骤后，我现在得到的错误回溯如下:

Traceback (most recent call last):
File "weather.py", line 40, in <module>
print(df[df['MaxTemperatureF' > 100]])
TypeError: unorderable types: str() > int()
Mikes-MBP-2:dataframes mikecuddy$ python3 weather.py
Traceback (most recent call last):
File "weather.py", line 41, in <module>
print(df[[df.MaxTemperatureF > 100 ]])
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-     
packages/pandas/core/frame.py", line 1991, in __getitem__
return self._getitem_array(key)
File "/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-  
packages/pandas/core/frame.py", line 2028, in _getitem_array
(len(key), len(self.index)))
 ValueError: Item wrong length 1 instead of 360.

我一直在做一个教程: http://www.gregreda.com/2013/10/26/working-with-pandas-dataframes/再次，任何帮助都会很棒!谢谢!

df.info() 信息:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 360 entries, 0 to 359
Data columns (total 23 columns):
PST                           360 non-null object
MaxTemperatureF               359 non-null float64
Mean TemperatureF             359 non-null float64
Min TemperatureF              359 non-null float64
Max Dew PointF                359 non-null float64
MeanDew PointF                359 non-null float64
Min DewpointF                 359 non-null float64
Max Humidity                  359 non-null float64
Mean Humidity                359 non-null float64
Min Humidity                 359 non-null float64
Max Sea Level PressureIn     359 non-null float64
Mean Sea Level PressureIn    359 non-null float64
Min Sea Level PressureIn     359 non-null float64
Max VisibilityMiles          355 non-null float64
Mean VisibilityMiles         355 non-null float64
Min VisibilityMiles          355 non-null float64
Max Wind SpeedMPH            359 non-null float64
Mean Wind SpeedMPH           359 non-null float64
Max Gust SpeedMPH            211 non-null float64
PrecipitationIn               360 non-null float64
CloudCover                   343 non-null float64
Events                       18 non-null object
WindDirDegrees               360 non-null int64
dtypes: float64(20), int64(1), object(2)
memory usage: 64.8+ KB
None

Answer 1

对于最高温度，您可以指定转换器函数:

df = pd.read_csv('csv/weather.csv', converters={'MaxTemperatureF':float})

编辑:正如@ptrj 在评论中提到的，您可以这样做来代替 np.nan对于 MaxTemperatureF 中的字符串值柱子:

df = pd.read_csv('csv/weather.csv', 
                 converters={'MaxTemperatureF':
                             lambda x: try: return float(x); 
                                       except ValueError: return np.nan;})

Edit2:@ptrj 的解决方案，因为他无法在评论中写出来...

def my_conv(x): 
    try: 
        return float(x)
    except ValueError: 
        return np.nan

df = pd.read_csv('csv/weather.csv', converters={'MaxTemperatureF': my_conv})

其他事情:

如果 csv 文件的第一行有标题，则不要通过 header=0 .

由于您现在已经有了标题，因此您无需指定 cols=...

默认sep是 ',' 所以你不需要指定它。