pandas 在操作数据帧时引发 ValueError('Series length must match to compare')
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raise ValueError('Series lengths must match to compare') while manipulating dataframe
提问by GothamCityRises
I'm a python beginner, and was writing code to manipulate a dataframe to aggregate rows that lie between two values. The value is extracted from one of the values in the dataframe itself.
我是一名 Python 初学者，正在编写代码来操作数据框以聚合位于两个值之间的行。该值是从数据帧本身的值之一中提取的。
a = df_gb1.loc[0,['TimeStamp']]
And i'm using a and a+0.4 as the two bounds to get all the rows.
我使用 a 和 a+0.4 作为获取所有行的两个边界。
df_gb1[df_gb1['TimeStamp'].between(a-0,a+0.4, inclusive=True)]
I don't know a better way to implement this, but it still gives me this error:
我不知道更好的方法来实现这一点，但它仍然给我这个错误：
Like I said before, I'm very new to python, so I don't quite know how datatypes work with one another. It seems as if ais Series as well.
就像我之前说的，我对 python 很陌生，所以我不太了解数据类型如何相互配合。好像a也是系列。
How do I implement what I'm trying to do?
我如何实施我正在尝试做的事情？
采纳答案by jezrael
I think you need remove []only for return scalar a, else output is Series:
我认为你[]只需要删除返回标量a，否则输出是Series：
df_gb1 = pd.DataFrame({'TimeStamp':[3,3.1,5,7.1,3.4],
'a':[4,5,6,7,8]})
print (df_gb1)
TimeStamp a
0 3.0 4
1 3.1 5
2 5.0 6
3 7.1 7
4 3.4 8
a = df_gb1.loc[0,'TimeStamp']
print (a)
3.0
print (df_gb1[df_gb1['TimeStamp'].between(a-0,a+0.4, inclusive=True)])
TimeStamp a
0 3.0 4
1 3.1 5
4 3.4 8
print (df_gb1.loc[0,['TimeStamp']])
TimeStamp 3.0
Name: 0, dtype: float64
