target, method, level, limit, tolerance)4426raiseValueError("cannot handle a non-unique multi-index!")4427elifnotself.is_unique:4428# GH#42568->4429raiseValueError("cannot reindex on an axis with duplicate labels")4430else:4431indexer, _ = self.get_indexer_non_unique(target) ...
We are supposed to find the unique values from multiple groupby. Getting unique values from multiple columns in a pandas groupby For this purpose, we can use the combination ofdataframe.groupby()andapply()method with the specifiedlambda expression. Thegroupby()method is a simple but very use...
Pandas内置丰富的库函数,支持多种结构化数据计算,包括:遍历循环apply\map\transform\itertuples\iterrows\iteritems、过滤Filter\query\where\mask、排序sort_values、唯一值unique、分组groupby、聚合agg(max\min\mean\count\median\ std\var\cor)、关联join\merge、合并append\concat、转置transpose、移动窗口rolling、shi...
for i in data: # 遍历数据集中的每一列 if pd.api.types.is_object_dtype(data[i]): # 如果是object类型的数据,则执行下方代码 data[i]=data[i].str.strip() # 去除空格data['origin'].unique() # 验证一下 输出结果:array([‘China’, ‘America’, ‘Thailand’, ‘america’, ‘Japan’], ...
Merge two rows of data and join values if unique - Pandas I am re-writing a VBScript that I wrote in Excel a while ago in Python Pandas. The reason for this is due to it breaking regularly as using VBS Macros in an Apple version of Microsoft Office is unstable. The script creates th...
("cannot handle a non-unique multi-index!") 4427 elif not self.is_unique: 4428 # GH#42568 -> 4429 raise ValueError("cannot reindex on an axis with duplicate labels") 4430 else: 4431 indexer, _ = self.get_indexer_non_unique(target) ValueError: cannot reindex on an axis with duplicate...
Dataframe 时，会出现该错误，并且它可以如下重现：四行数据框：
2. Count of unique values in each row You can also get the count of distinct values in each row by setting theaxisparameter to1or'columns'in thenunique()function. # count of unique values in each row print(df.nunique(axis=1))
index =None,# 行索引默认columns=['Python','Math','En'])# 列索引# shape - 数据形状r1 = df.shape# (150, 3)print('数据形状:') display(r1)# dtypes - 数据类型r2 = df.dtypesprint('数据类型:') display(r2) index/columns/values - 查看索引 - 行/列/属性 ...
).cumcount() +1).astype() df.pivot_table(index="device_id", values=cols_of_interest, columns="C") temp_a temp_b temp_c C C_1 C_2 C_3 C_1 C_2 C_3 C_1 C_2 C_3 device_id00.20.1NaN0.80.40.9