Advertisements Exist a data frame with events start_ event end_event 1 2023-09-23 17:20 2023-09-23 17:40 2 2023-09-24 10:00 2023-09-24 10:20 3 2023-09-24 10:20 2023-09-24 10:40 4 2023-09-24 10:40 2023-09-24 11:00 5 2023-09-25 11:00 2023-09-25 11:20 6 2023-09-25 11:20 2023-09-25 11:40 Difference between start_ event and end_event always 20 minutes. I need to group the data… Read More Changing row value based on previous row value

Advertisements I need to filter a large dataset of variables with entries for multiple dates. In this instance I want to keep only data entered on the very first date. For example in the dataset below: dfex = pd.DataFrame({‘names’:[‘jim’,’jim’,’jim’,’jim’,’jim’,’jim’,’jim’,’jim’,’jim’, ‘bob’,’bob’,’bob’,’bob’,’bob’,’bob’, ‘sara’,’sara’,’sara’,’sara’,’sara’,’sara’,’sara’,’sara’,’sara’,’sara’], ‘dates’:[’01-01-19′,’01-01-19′,’01-01-19′,’01-05-19′,’01-06-19′,’01-07-19′,’01-08-19′,’01-09-19′,’01-10-19′, ’01-05-19′,’01-05-19′,’01-07-19′,’01-08-19′,’01-09-19′,’01-10-19′, ’01-02-19′,’01-02-19′,’01-02-19′,’01-02-19′,’01-05-19′,’01-06-19′,’01-07-19′,’01-08-19′,’01-09-19′,’01-10-19′]}) dfex[‘dates’] = pd.to_datetime(dfex[‘dates’]) dfex jim would keep the first 3 rows,… Read More Filter pandas dataframe for first N unique values per group

Advertisements I’m looking a way to use groupby on a dataframe that contains datetime64 format on some columns. But im having this error: dfsum = df.groupby([‘City’]).sum() TypeError: datetime64 type does not support sum operations I tried using: desired = df.select_dtypes(include=[int, float, object]) dfsum_city = desired.groupby([‘City’]).sum() dfsum_city.reset_index(inplace=True) But i dont think it is the right way… Read More Exclude datetime from GroupBy sum

Advertisements Working on a PHP form that sends date I create a time/date from a input form. (jquery datepicker) $dateinput = $_POST[‘datepicker’]; $t1 = date_create($dateinput); //times are posted seperate and stipped from a input box (either 1055 or 10:55) $t1_hour = substr($t1_raw,0,2); $t1_min = substr($t1_raw,-2); $t1->add(new DateInterval(‘PT’ . $t1_hour . ‘H’)); $t1->add(new DateInterval(‘PT’ . $t1_min… Read More Failing to format my date to work correctly in php

Advertisements I am trying to change the format of a datetime column from ‘YYYY-MM-DD HH-MM-SS’ to ‘YYYY-DD-MM HH-MM-SS’ input: 2023-04-12 07:15:10 script that is used in a select statement: TO_CHAR(TO_DATE(a.time_stamp, ‘YYYY-MM-DD HH24:MI:SS’), ‘YYYY-DD-MM HH24:MI:SS’) as CHANGE_TIME output: 0012-23-04 00:00:00 desired output: 2023-12-04 07:15:10 >Solution : That’s because you applied to_date function to value that already… Read More Changing datetime format in sql

Advertisements I have a dataset and I need to remove IDs entirely that are flagged before a certain date and beyond. I am having trouble getting a start on this one. df = ID Date Flagged 101 6/4/2023 0 101 7/23/2023 0 102 4/28/2023 1 102 5/2/2023 1 102 6/30/2023 1 102 7/11/2023 1 103… Read More Removing IDs under specific conditions in Python

Advertisements I am trying to integrate with some VB code that generates a string using DateTime.Now.ToString("yyyyMMddHHmmssffff") The closest I can get to this in PHP has been date(‘YmdHis’) But this lacks the milliseconds, I have tried playing with microtime e.g. date(‘YmdHis’,time()).substr(str_replace(".","",microtime(true)),10,17) But sometimes this results in a shorter string >Solution : date function always returns… Read More How to create a string in PHP that is equivalent to yyyyMMddHHmmssffff

Advertisements I am running the following code: filled_df = (ts.set_index(date_col) .groupby(grouping) .apply(lambda d: d.reindex( pd.date_range( mf_heuristic(d.index, champion_end), pd.to_datetime( dt.datetime.now() ), freq=’MS’) ) ) .drop(grouping, axis=1) .reset_index(grouping) .fillna(0) with the predefinitions: date_col = ‘timepoint’ grouping = [‘Level’, ‘Kontogruppe’] champion_end = fc_date – pd.DateOffset(months=13) print(champion_end) 2021-03-01 00:00:00 print(ts) Kontogruppe Level timepoint data_value 0 A ZBFO 2020-03-01 1… Read More datetime struggle with a pandas dataframe

Advertisements I have not been able to figure out the date format to detect the date string of August 20, 2022 I have attempted using this format month dd, yyyy to detect it however it is not working. I have several dates in my file formatted in this manner. Currently my script is missing these… Read More What is the correct Date Format String for Month DD, YYYY to use in Powershell

Advertisements I have date time in the format YYYY/DOY/HHMM DOY = Day of year I tried to parse as follows. from datetime import datetime s = "1929/189/1820" res = datetime.strptime(s, "%y/%j/%H%M") print (res) ValueError: time data ‘2029/199/1820’ does not match format ‘%y/%j/%H%M’. >Solution : The Y for year should be capitol This should fix it.… Read More On parsing datetime, ValueError: time data does not match format