在熊猫蟒蛇中掉落NaN
问题描述:
不知道为什么.dropnan()
不会删除带有NaN值的单元格?在熊猫蟒蛇中掉落NaN
请帮忙,我已经通过了熊猫文档,不知道我在做什么错?
import pandas as pd
import quandl
import pandas as pd
df = quandl.get("GOOG/NYSE_SPY")
df2 = quandl.get("YAHOO/AAPL")
date = pd.date_range('2010-01-01', periods = 365)
df3 = pd.DataFrame(index = date)
df3 = df3.join(df['Open'], how = 'inner')
df3.rename(columns = {'Open': 'SPY'}, inplace = True)
df3 = df3.join(df2['Open'], how = 'inner')
df3.rename(columns = {'Open': 'AAPL'}, inplace = True)
df3['Spread'] = df3['SPY']/df3['AAPL']
df3 = df3/df3.ix[0]
df3.dropna(how = 'any')
df3.plot()
print(df3)
答
变化df3.dropna(how = 'any')
到df3 = df3.dropna(how = 'any')
答
我试图用一个简单的csv文件来复制你的问题:
In [6]: df
Out[6]:
a b
0 1.0 3.0
1 2.0 NaN
2 NaN 6.0
3 5.0 3.0
两个df.dropna(如何= '任何')以及DF1 = df.dropna(how ='any')的工作。即使只是df.dropna()的作品。我想知道你的问题是否是因为你在前面的线进行划分:
df3 = df3/df3.ix[0]
df3.dropna(how = 'any')
举例来说,如果我通过df.ix [1]划分,因为元素之一是NaN,将其转换将结果中的所有元素都纳入NaN,然后如果使用dropna删除NaN,则会删除所有行:
In [17]: df.ix[1]
Out[17]:
a 2.0
b NaN
Name: 1, dtype: float64
In [18]: df2 = df/df.ix[1]
In [19]: df2
Out[19]:
a b
0 0.5 NaN
1 1.0 NaN
2 NaN NaN
3 2.5 NaN
In [20]: df2.dropna()
Out[20]:
Empty DataFrame
Columns: [a, b]
Index: []
它不是就地操作。无论是'df3.dropna(how ='any',inplace = True)'或'df3 = df3.dropna(how ='any')'都可以工作。 – ayhan