join

问题 I have 2 dataframes das <- data.frame(val=1:20, type =c("A","A","A","A","A","A","B","B","B","B","B","B","B","B","B","B","C","C","C","C"), weigh=c(20,22,23,32,34,54,19,22,24,26,31,34,36,37,51,54,31,35,43,45)) mapper <- data.frame(type=c("A","A","A","A","B","B","B","B","C","C","C","C"),start = c(19,23,27,37 ,17,25,39,50, 17,23,33,39),end = c(23,27,37,55 ,25,39,50,60, 23,33,39,48)) The expected output is val type weigh labelweight 1 1 A 20 A_19 2 2 A 22 A_19 3 3 A 23 A_23 4 4 A 32 A_27 5 5 A 34

问题 I have 2 dataframes das <- data.frame(val=1:20, type =c("A","A","A","A","A","A","B","B","B","B","B","B","B","B","B","B","C","C","C","C"), weigh=c(20,22,23,32,34,54,19,22,24,26,31,34,36,37,51,54,31,35,43,45)) mapper <- data.frame(type=c("A","A","A","A","B","B","B","B","C","C","C","C"),start = c(19,23,27,37 ,17,25,39,50, 17,23,33,39),end = c(23,27,37,55 ,25,39,50,60, 23,33,39,48)) The expected output is val type weigh labelweight 1 1 A 20 A_19 2 2 A 22 A_19 3 3 A 23 A_23 4 4 A 32 A_27 5 5 A 34

问题 The following image can be found by searching for SQL join on the internet: Can we interpret this as a Venn diagram, in the following way? The circle labelled Table A is the set of records in Table A The circle labelled Table B is the set of records in Table B The intersection of the sets represents inner join (aka just join in SQL) Motivation The diagram shown, which appears in various forms widely on the net, looks awfully like a Venn diagram. So the first intuition is to think of it as a

问题 I have (more than) two dataframes: In [22]: df = pd.DataFrame({'database' : ['db1', 'db2', 'db3']}) In [23]: df1 = pd.DataFrame({'database' : ['db1', 'db2', 'db3']}) In [24]: df2 = pd.DataFrame({'database' : ['db2', 'db3', 'db4']}) In [25]: df1 Out[25]: database 0 db1 1 db2 2 db3 In [26]: df2 Out[26]: database 0 db2 1 db3 2 db4 What I want as output is dataframe in this format: Out[45]: database database 0 db1 1 db2 db2 2 db3 db3 3 db4 I manage to get it in this format like this: df1.index =

问题 I want to join a list of tuples within a dataframe. I have tried several methods of doing this within the dataframe with join and with lambda import pandas as pd from nltk import word_tokenize, pos_tag, pos_tag_sents data = {'Categories': ['animal','plant','object'], 'Type': ['tree','dog','rock'], 'Comment': ['The NYC tree is very big', 'NY The cat from the UK is small', 'The rock was found in LA.']} def posTag(data): data = pd.DataFrame(data) comments = data['Comment'].tolist()

问题 Is there a better way of the following for concatenating items in a list that are "integers" into a string: import numpy as np my_list = [1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0] changed_list = np.char.mod('%d', my_list) final_ans = ''.join(changed_list ) 回答1: Im not sure what you mean by better, but you could try this. ''.join([str(x) for x in my_list]) 回答2: how about this? ''.join([str(item) for item in my_list]) 回答3: You can use the bitstring module: >>> from bitstring import BitArray >>> f'

问题 I have a table of revenue as title_id revenue cost 1 10 5 2 10 5 3 10 5 4 10 5 1 20 6 2 20 6 3 20 6 4 20 6 when i execute this query SELECT SUM(revenue),SUM(cost) FROM revenue GROUP BY revenue.title_id it produces result title_id revenue cost 1 30 11 2 30 11 3 30 11 4 30 11 which is ok, now i want to combine sum result with another table which has structure like this title_id interest 1 10 2 10 3 10 4 10 1 20 2 20 3 20 4 20 when i execute join with aggregate function like this SELECT SUM

问题 I have a table of revenue as title_id revenue cost 1 10 5 2 10 5 3 10 5 4 10 5 1 20 6 2 20 6 3 20 6 4 20 6 when i execute this query SELECT SUM(revenue),SUM(cost) FROM revenue GROUP BY revenue.title_id it produces result title_id revenue cost 1 30 11 2 30 11 3 30 11 4 30 11 which is ok, now i want to combine sum result with another table which has structure like this title_id interest 1 10 2 10 3 10 4 10 1 20 2 20 3 20 4 20 when i execute join with aggregate function like this SELECT SUM

问题 I have three tables: Orders OrderId, int PK CustomerId, int FK to Customer, NULL allowed Customers CustomerId, int PK CompanyId, int FK to Company, NULL not allowed Companies CompanyId, int PK Name, nvarchar(50) I want to select all orders, no matter if they have a customer or not, and if they have a customer then also the customer's company name. If I use this query... SELECT Orders.OrderId, Customers.CustomerId, Companies.Name FROM Orders LEFT OUTER JOIN Customers ON Orders.CustomerId =

问题 I have three tables: Orders OrderId, int PK CustomerId, int FK to Customer, NULL allowed Customers CustomerId, int PK CompanyId, int FK to Company, NULL not allowed Companies CompanyId, int PK Name, nvarchar(50) I want to select all orders, no matter if they have a customer or not, and if they have a customer then also the customer's company name. If I use this query... SELECT Orders.OrderId, Customers.CustomerId, Companies.Name FROM Orders LEFT OUTER JOIN Customers ON Orders.CustomerId =