Advertisements I have the below DF that contains Lookup Definition A Apple B Banana C Carrot I have another DF2: SNo Lookup Values 1 [‘A’, ‘B’] 2 [‘A’, ‘C’] 3 [‘B’, ‘C’] Note: "Lookup Values" column is a list of strings What is the most simple way of performing the JOIN to get the below:… Read More Merge two DataFrames based on a string aggregated column

Advertisements I have this df1 library(dplyr) library(tidyverse) df1 = data.frame(ID = c(100,101,101,102,102,103,103,104,104,105,106), x_line = c(1,1,2,1,2,1,2,1,2,1,1), start_date = c(’04/01/2018′,’05/01/2019′,’25/08/2021′,’08/03/2017′,’07/08/2018′, ’09/04/2016′,’29/12/2018′,’04/08/2018′,’03/05/2022′,’04/01/2018′,’04/01/2018′), end_date = c(’04/05/2019′,’07/02/2020′,’27/09/2021′,’18/07/2018′,’17/10/2019′, ’19/12/2018′,’22/12/2019′,’14/09/2021′,’26/12/2022′,’15/02/2020′,’24/08/2020′) ) and the following df2 df2 = data.frame(ID = c(100,100,100,101,101,102,102,103,103,104,104,105,105,106,106,106), product_name = c(‘AA’,’BB’,’CC’,’AA’,’CC’,’DD’,’EE’,’DD’,’FF’, ‘AA’,’FF’,’DD’,’AA’,’CC’,’AA’,’BB’), start_taken_date = c(’04/05/2018′,’25/08/2018′,’27/09/2018′,’18/07/2019′,’25/11/2019′, ’29/01/2018′,’07/09/2018′,’14/09/2017′,’01/01/2019′,’15/02/2019′,’24/08/2020′, ’04/03/2019′,’04/08/2018′, ’05/05/2018′,’06/06/2019′,’08/09/2018′), end_taken_date = c(’01/05/2019′,’26/09/2018′,’25/03/2019′,’25/09/2019′,’02/01/2020′, ’19/06/2018′,’22/09/2019′,’16/01/2018′,’04/03/2019′,’25/06/2022′,’23/07/2022′, ’05/04/2019′,’05/09/2018′, ’29/03/2019′,’07/07/2019′,’04/05/2020′)) df3 is the result of merging… Read More How to merge two dataframes based on the condition of a startdate and enddate?

Advertisements I’m trying to replace values in a dataframe based on values in a different dataframe. Below you will find a simple data sample: df1 old_index Date 0 3 2019-10-23 1 19 2019-12-05 2 29 NaT 3 32 NaT 4 34 2019-12-05 5 116 NaT 6 118 2020-01-29 df2 old_index Date 4 3 2019-10-24 12… Read More Merge not giving the desired result when replacing values in a dataframe based on a match in another dataframe

Advertisements I have a situation similar to this one: I have two datasets, this one: from to frequency a a 2 a b 3 and this one: from to frequency a a 3 a b 4 Now, I want to merge the two, keeping "from" and "to" variables the same, since they are exactly the… Read More Merging two datasets summing a shared column

Advertisements I have a 2 datasets with two different shapes and column names and I need to merge them to fill the blanks in for all the NaNs. When I try and doesn’t work and I am left with NaNs still. Here is a sample: DF1: ID Mgr_name Reports EmpType mgr_pos_num 101 NaN 3 Manager… Read More How to merge two datasets of different shapes with different column names in python

Advertisements I have two dataframes that look like below proj_df = pd.DataFrame({‘reg_id’:[1,2,3,4], ‘part_no’:[‘P1′,’P2′,’P3′,’P4’], ‘partner’:[‘A’,’B’,’C’,’D’], ‘cust_name_1’: [‘ABC PVT LTD’,’Tesla’,’Apple’,’Google’], ‘cust_name_2’:[‘ABC’,’Tesla Ltd’,’Apple Inc’,’Google Enterprises’], ‘cust_name_3’:[‘ABC’,’Tesla America’,’Apple America’,’Google Ent Pvt ltd’]}) data_df = pd.DataFrame({‘cust_name’: [‘ABC’,’Tesla America’,’Apple Inc’,’Google’,’Google’,’ABC’], ‘partner’:[‘A’,’B’,’C’,’D’,’E’,’A’], ‘part_no’:[‘P1′,’P2′,’P3′,’P4′,’P5′,’P6’], ‘qty’:[100,100,600,150,320,410]}) I would like to do the below a) Identify the exactly matching customer name column from proj_df by… Read More Pandas create a new column based on exact match of text values

Advertisements I have a txt file like below, 140037|1|TOP SOIL DARK BROWN CLAY RICH ORGANIC|0|0.8 140037|2|MATER SOFT|| 140037|3|SANDY CLAY SOFT MOTTLED GREY/ORANGE|0.8|1 140037|4|BROWN <15% SAND GRAINS|| 140037|5|CLAY MOTTLED DARK GREY/ORANGE BROWN|1|3 140037|6|SOFT BECOMING FIRM MINOR SILT AND|| 140037|7|FINE SAND IN SOME LAYERS|| and want to make it like this. 140037|1|TOP SOIL DARK BROWN CLAY RICH… Read More Merge two or more lines of text into one line with python pandas

Advertisements I’m trying to figure out how to achieve the following. Say that I have a master dataframe with an ID column and various other data: ID A B C 01 1x 1y 1z 02 2x 2y 2z 03 3x 3y 3z 04 4x 4y 4z … 01000 01000x 01000y 01000z And I additionally have… Read More Pandas: Update master dataframe with additional columns, with growing number of common columns in subsequent merges

Advertisements I have two dataframes: df1 name year name_1 2018 name_2 2017 name_3 2021 name_1 2022 . . . and: df2 name start end id name_1 2017 2021 1 name_2 2017 2022 2 name_1 2022 2023 3 Now I want to add the id of each name into df1 from df2 based on the following… Read More merge two dataframes based on condition and get id

Advertisements I am trying to merge multiple lists that outputs 1 list of all the values and keep the zeros. The indices and values need to be kept in the same index location. Input: list1 = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0] list2 = [0, 0, 0, 0, 0,… Read More How to compress multiple lists into one list and keeping the same size list?