我在词典中有词典。我的问题陈述是，我想对字典中的键（or和'filter'）0索引执行'filteer'操作。基于该结果，我想对字典中索引1中的特定列应用groupby操作。
（例如，如果brand（conditions [0]）== AMBI（conditions [8]）
（或）Manufacturer（conditions [1]）== AMBI（conditions [8]）我想返回数据框，并希望在该数据框上对列之一执行groupby操作。）
我的代码：
import csv
import pandas as pd
import sys
class sample:
def create_df(self, f):
self.z=pd.read_csv(f)
def get_resultant_df(self, list_cols):
self.data_frame = self.z[list_cols[:]]
def process_df(self, df, conditions):
resultant_df = self.data_frame
if conditions[2] == 'equals':
new_df =resultant_df[resultant_df[conditions[1]] == conditions[3]]
return new_df
elif conditions[2] == 'contains':
new_df = resultant_df[resultant_df[conditions[1]].str.contains(conditions[3])]
return new_df
elif conditions[2] == 'not equals':
new_df = resultant_df[resultant_df[conditions[1]] != conditions[3]]
return new_df
elif conditions[2] == 'startswith':
new_df = resultant_df[resultant_df[conditions[1]].str.startswith(conditions[3])]
return new_df
elif conditions[2] == 'in':
new_df = resultant_df[resultant_df[conditions[1]].isin(resultant_df[conditions[3]])]
return new_df
elif conditions[2] == 'not in':
new_df = resultant_df[~resultant_df[conditions[1]].isin(resultant_df[conditions[3]])]
return new_df
elif conditions[2] == 'group':
new_df = list(resultant_df.groupby(conditions[0])[conditions[1]])
return new_df
elif conditions[2] == 'specific':
new_df = resultant_df.loc[resultant_df[conditions[0]] == conditions[8]]
return new_df
elif conditions[2] == 'same':
new_df = resultant_df[(resultant_df[conditions[0]] == conditions[8]) & (resultant_df[conditions[1]] == conditions[8])]
return new_df
elif conditions[2]=='trail':
new_df={0:{'filter'{'filter1':resultant_df.loc[resultant_df[conditions[0]] == conditions[8]]},'filteer':{'filter1':resultant_df.loc[resultant_df[conditions[0]] == conditions[8]]}},
1:{'group':{resultant_df.groupby(new_df[0][filter])}}}
return new_df
if __name__ =='__main__':
sample = sample()
sample.create_df("/home/purpletalk/GrammarandProductReviews.csv")
df = sample.get_resultant_df(['brand', 'reviews.id','manufacturer','reviews.title','reviews.username','id','dateAdded','reviews.rating'])
new_df = sample.process_df(df, ['brand','manufacturer','trail','Windex', 'size', 'equal',8,700,'AMBI'])
print (new_df[1][group])
可以请人帮我吗？上面的代码返回错误，我想知道如何执行or操作。