'str'对象不能解释为groupby上的整数

Can someone please explain why I'm getting this error when I'm doing a lingress (slope) on 'day' and 'value' which are both numeric datatype. Below is my script:

有人可以解释为什么我在'day'和'value'上做一个lingress(斜坡)时都会出现这个错误,这两个都是数值数据类型。以下是我的脚本:

import pandas as pd
from scipy.stats import linregress
y = pd.DataFrame({'entity':['a','a','b','b','b','c'],
                          'day':[1999,2004,2003,2007,2014, 2016],
                          'value':[2,5,3,2,7,8]})
mylist= ['a', 'b'] 
y1 = y.groupby('entity').apply(lambda x: x[x['entity'].isin(mylist)])

This line gives error:

这一行给出错误:

y1.apply(lambda v: linregress(v['day'], v['value']))

error trace:

TypeError Traceback (most recent call last) /anaconda3/lib/python3.6/site-packages/pandas/core/indexes/multi.py in get_value(self, series, key) 999 try: -> 1000 return libindex.get_value_at(s, k) 1001 except IndexError:

TypeError Traceback(最近一次调用最后一次)/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/multi.py in get_value(self,series,key)999试试: - > 1000 return libindex.get_value_at( s,k)1001除了IndexError:

pandas/_libs/index.pyx in pandas._libs.index.get_value_at()

pandas._libs.index.get_value_at()中的pandas / _libs / index.pyx

pandas/_libs/src/util.pxd in util.get_value_at()

util.get_value_at()中的pandas / _libs / src / util.pxd

TypeError: 'str' object cannot be interpreted as an integer

TypeError:'str'对象不能解释为整数

During handling of the above exception, another exception occurred:

在处理上述异常期间,发生了另一个异常:

KeyError Traceback (most recent call last) in () ----> 1 y1.apply(lambda v: linregress(v['day'], v['value'])) 2

KeyError Traceback(最近一次调用last)in()----> 1 y1.apply(lambda v:linregress(v ['day'],v ['value']))2

KeyError: ('day', 'occurred at index entity')

KeyError :('day','发生在索引实体')

2 个解决方案

#1

Update, then you need this:

更新,然后你需要这个:

y1.groupby(level='entity').apply(lambda x: linregress(x['day'],x['value']))

Output:

entity
a                                                                 (0.6, -1197.3999999999999, 1.0, 0.0, 0.0)
b    (0.4032258064516129, -805.6774193548387, 0.8485552916276634, 0.35494576760559776, 0.25142673013096595)
dtype: object

I think all you need is to do this, you do not need to apply, just pass the two dataframe columns to linregress:

我认为您只需要执行此操作,您不需要应用,只需将两个数据帧列传递给linregress:

linregress(y1['day'],y1['value'])

Output:

LinregressResult(slope=0.29073482428115016, intercept=-579.2396166134187, rvalue=0.7502746874224853, pvalue=0.14406233411953523, stderr=0.1479110164470003)

2 个解决方案

#1

更多相关文章

随机推荐