Advertisements data = {‘ITEM’: [‘a’, ‘a’, ‘a’, ‘a’, ‘a’, ‘b’, ‘b’, ‘b’, ‘c’, ‘c’, ‘d’, ‘z’, ‘z’, ‘z’, ‘z’], ‘col1’: [37, 84, 54, 72, 49, 20, 64, 75, 90, 71, 84, 46, 78, 24, 34], ‘col2’: [27, 44, 43, 12, 92, 10, 24, 55, 50, 37, 44, 57, 38, 64, 17], ‘col3’: [17, 54, 64,… Read More Pandas Want combine Statistics data using groupby
Advertisements I have a multi-indexed pandas dataframe with two indices. The first index is ‘room’, the second is ‘timestamp’. The columns of this table are ‘total occupancy’, ‘temperature’, ‘power used’ and ‘event’. The situation being tracked is consider a hotel with several ball rooms. these rooms get booked for events. Periodically, hotel mngmt records the… Read More How to get range of values in secondary index of pandas dataframe
Advertisements I have a dataset where there are groups ‘gr1’, ‘gr2’, and ‘both’. Basically, I’d like to group the ‘gr’ column by c("gr1", "both") and c("gr2", "both"). Here I’m proposing a solution with a simple data frame, but I’d like to know if there is a way to make ‘complex’ grouping such as group_by(gr ”using… Read More Group by an overlapping category (a category should be grouped in 2 different other categories)
Advertisements I have a dataset and I need to get the sum from two other columns and group them by name. DF a b c Joe 1 0 Joe 1 0 Joe 0 1 Adam 1 0 Adam 0 1 Adam 0 0 Desired Output: a b c d Joe 1 0 1 Joe 1… Read More Creating a column with sum of multiple columns grouped by name in panda
Advertisements I have a list which I am trying to group by the first element of the nested list. The problem is that my code is not recognising that there are only 5 different values among the grouped on element. a = [[‘2.25.151989603747108360484758994222924880510’, 1], [‘2.25.23907329898781253437777953862543062317’, 1], [‘2.25.151989603747108360484758994222924880510’, 2], [‘2.25.23907329898781253437777953862543062317’, 1], [‘2.25.159215431212584126451402597802236328925’, 1], [‘2.25.339018106044083012102817776589396922392’, 1], [‘2.25.159215431212584126451402597802236328925’,… Read More Python groupby function not recognising that there are keys that are identical that can be "grouped on"
Advertisements So I have some complicated analysis to do. I have this data in a df: Date/Time TimeStamp CallerId CallType watts Band slot Channel 0 20:02.0 3113677432 17794800 C1 0.060303 12 1 2 1 20:02.0 3113677432 5520488 OP8 0.302229 12 1 1 2 20:02.0 3113677432 5520488 OP8 0.302229 13 1 1 3 20:02.0 3113677432 5520488… Read More pandas- create new series from multilevel columns and aggregate
Advertisements I have a datafrmame: user_id object local time datetime64[ns] value int32 user_id local time value 0 user1 2023-01-01 00:00:00 3 1 user1 2023-01-01 00:00:00 3 2 user1 2023-01-01 01:00:00 7 3 user1 2023-01-01 01:00:00 2 4 user2 2023-01-01 02:00:00 4 5 user2 2023-01-01 02:00:00 10 6 user2 2023-01-01 03:00:00 7 7 user2 2023-01-01 03:00:00… Read More groupby mean of datetime64[ns] column
Advertisements I need to check if the value inside "CP" columns of a dataframe, while my dataframe is grouped by "Centre" column, are canceling each others. Here is an example : Sample : Centre CP 3N7D 10 3N1F 2 3N90 -9 3N7D -1 3N7D -10 8D92 198 3N7D -10 3N90 2 8D92 -195 8D92 -3… Read More Group values and check if the values from another column cancel each other out in python pandas dataframe
Advertisements I have a piece of code that should be getting the first_team (first value) of a column grouped by ID and setting it to a dictionary, but what I am seeing is it is only getting the first value with value. Excluding those that are NaN. Here is a sample dataset ID date name… Read More Getting first row by ID in Python
Advertisements So I have this table and in SQL as below Table : Fruits Id = int, Name = varchar, Type = varchar, isPrimary = bit Id Name Type isPrimary 1 Apple Type A 1 2 Apple Type B 0 3 Mango Type A 0 4 Mango Type B 0 5 Mango Type C 1… Read More To check if group of records contain a boolean in SQL