Advertisements I have the following file: 2 1 4 3 2 1 I want the output like this (unique lines that don’t have any duplicates and preserve order): 4 3 I tried sort file.txt | uniq -u it works, but output is sorted: 3 4 I tried awk ‘!x[$0]++’ file.txt it keeps order, but it… Read More Print lines that have no duplicates in a file and preserve sort order linux
Advertisements As a language that aims for safety and performance, Rust provides a powerful data structure called HashSet that provides a fast and efficient way to store and retrieve unique values. HashSet is optimized for scenarios where you need to check for the presence of a value and avoid duplicates, making it a popular choice… Read More How to apply function that returns Result to each element of HashSet in Rust
Advertisements I have a dataset, df, that looks like this: Date Code City State Population Quantity QTDPERCAPITA 2020-01 11001 Los Angeles CA 5000000 100000 0.02 2020-02 11001 Los Angeles CA 5000000 125000 0.025 2020-03 11001 Los Angeles CA 5000000 135000 0.027 2020-01 12002 Houston TX 3000000 150000 0.05 2020-02 12002 Houston TX 3000000 100000 0.033… Read More How to create a ranking variable/function for different periods in a panel data?
Advertisements I have an image of a color scale I filter out the actual color scale by using import cv2 import numpy as np colorbar = cv2.imread(‘colorbar-scheme-elevation.png’, cv2.IMREAD_UNCHANGED) colorbar = cv2.cvtColor(colorbar, cv2.COLOR_BGRA2BGR) hsv = cv2.cvtColor(colorbar, cv2.COLOR_RGB2HSV) lower_gray = np.array([0, 0, 0]) upper_gray = np.array([255, 10, 255]) mask = cv2.inRange(hsv, lower_gray, upper_gray) mask = cv2.bitwise_not(mask) res… Read More Recreate colormap based on colorscale in matplotlib
Advertisements I have a dataframe column like this: df[‘col_name’].unique() >>>array([-1, ‘Not Passed, On the boundary’, 1, ‘Passed, On the boundary’, ‘Passed, Unclear result’, ‘Passes, Unclear result, On the boudnary’, ‘Rejected, Unclear result’], dtype=object) In this column, if an element contains the word ‘Passed’ as a field or as a substring, then replace the entire field… Read More Dataframe conditional replacement with intigers
Advertisements Since I’ve upgraded the BillingClient to version 5.0.0: googleImplementation ‘com.android.billingclient:billing:5.0.0’ I get these unique deprecation warnings: warning: [deprecation] getSkus() in Purchase has been deprecated warning: [deprecation] getSkus() in PurchaseHistoryRecord has been deprecated warning: [deprecation] SkuType in BillingClient has been deprecated warning: [deprecation] SkuDetailsResponseListener in com.android.billingclient.api has been deprecated warning: [deprecation] SkuDetailsParams in com.android.billingclient.api has… Read More Google Play Billing Library 5.0 deprecation warnings
Advertisements This question is most likely common and has been asked before. So, after spending a mind-numbing 30 minutes trying to find the solution to what I believe is a false negative, I’m resulting to posting my issue here. I’m relatively new to C++ Coding and figured I’d create a simple random item generator. Unfortunately,… Read More Resolving potential false negative C6385 Error in C++
Advertisements I would like to count how many new unique users the database gets each day for all days recorded. There will not be any duplicate ids per day, but there will be duplicates over multiple days. If my table looks like this : ID | DATE ——— 1 | 2022-05-21 1 | 2022-05-22 2… Read More MySQL – Count unique users each day considering all previous days
Advertisements I have a dataframe like as shown below id,Name,country,amount,qty 1,ABC,USA,123,4500 1,ABC,USA,156,3210 1,BCE,USA,687,2137 1,DEF,UK,456,1236 1,ABC,nan,216,324 1,DEF,nan,12678,11241 1,nan,nan,637,213 1,BCE,nan,213,543 1,XYZ,KOREA,432,321 1,XYZ,AUS,231,321 sf = pd.read_clipboard(sep=’,’) I would like to do the below a) Get top 3 based on amount for each id and other selected columns such as Name and country. Meaning, we get top 3 based… Read More Dynamic top 3 and percentage total using pandas groupby
Advertisements I’m new to R and have scoured the site to find a solution – I’ve found lots of similar, but slightly different questions. I’m stumped. I have a dataset in this structure: SURVEY_ID CHILD_NAME CHILD_AGE Survey1 Billy 4 Survey2 Claude 12 Survey2 Maude 6 Survey2 Constance 3 Survey3 George 22 Survey4 Marjoram 14 Survey4… Read More Pivot_wider: Combine Duplicate Observations AND Create New Variable Columns for Those Values