Python inequality join with group by Question: I have the following two dataframes import pandas as pd dates = [’31-12-2015′, ’31-12-2016′, ’31-12-2017′, ’31-12-2018′] df1 = pd.DataFrame({‘id’: [1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4], ‘t’: dates*4, ‘stage’: [1,2,2,3,1,1,2,3,1,1,1,3,2,1,1,3]}) df2 = df1.loc[df1[‘stage’] == 1] What is the most efficient way of doing the operation below in python? Select a.id ,a.t ,max(b.stage = 2) …
How to left join numpy array python Question: What’s the numpy "pythonic" way to left join arrays? Let’s say I have two 2-D arrays that share a key: a.shape # (20, 2) b.shape # (200, 3) Both arrays share a common key in their first dimension: a[:, 0] # values from 0..19 b[:, 0] # …
How is the Merge function reading the boolean (or/and) here? Question: I am trying to merge two dataframes if the right_on matches with any of the left_on columns. Dataframe examples: df_test_1 = pd.DataFrame({‘A’:[‘S1′,’S2′,’S3′,’S4′,’S5’], ‘B’:[‘S6′,”,”,’S7’,”], ‘C’:[10,11,12,13,14]}) df_test_2 = pd.DataFrame({‘D’:[‘S1′,’S2′,’S3′,’S5′,’S7′,’S9’], ‘E’:[1,2,3,4,5,6]}) Merging this way through or gives this output: pd.merge(df_test_1,df_test_2,left_on=[‘A’ or ‘B’],right_on=[‘D’],how=’left’) A B C D E …
(Pandas) How to replace certain values of a column from a different dataset but leave other values in the dataset untouched? Question: Let’s say I have the dataset: df1 = pd.DataFrame() df1[‘number’] = [0,0,0,0,0] df1["decade"] = ["1970", "1980", "1990", "2000", "2010"]` print(df1) #output: number decade 0 0 1970 1 0 1980 2 0 1990 3 …
Left join table without duplicating right table row values Question: I have 2 dataframe’s as below. I want to join right side table (cycletime) to left table (current data). Left Table- Current data (df_current) | datetime_index | current | speed | cycle_counter | |————————–|———|——-|—————| | 27-10-2022 08:30:56.3056 | 30 | 60 | 1 | | …
MySQL One-to-Many to JSON format Question: I have two MySQL tables: User (id, name) Sale (id, user, item) Where Sale(user) is a foreign key to User(id), so this is a one-to-many relationship (one user can make many sales). I’m trying to get this from the database and return it in JSON format for multiple users, …
Combine two pandas Data Frames (join on a common column) Question: I have 2 dataframes: restaurant_ids_dataframe Data columns (total 13 columns): business_id 4503 non-null values categories 4503 non-null values city 4503 non-null values full_address 4503 non-null values latitude 4503 non-null values longitude 4503 non-null values name 4503 non-null values neighborhoods 4503 non-null values open 4503 …
