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I have a dataframe, i am trying to remove the rows that are present in >= 3 groups. In my below example bike is the common value across 3 group and i need to remove that. Please help me to achieve this.
df <- data.frame(a = c("name1","name1","name1","name2","name2","name2","name3"), b=c("car","bike","bus","train","bike","tour","bike")) df a b name1 car name1 bike name1 bus name2 train name2 bike name2 tour name3 bike
a b name1 car name1 bus name2 train name2 tour
You can use
n_gr <- 3 cn <- df %>% group_by(b) %>% summarise(na = n_distinct(a)) %>% filter(na >= n_gr) %>% pull(b) df <- df %>% filter(!(b %in% cn))
a b 1 name1 car 2 name1 bus 3 name2 train 4 name2 tour
SQL Server DELETE, To remove one or more rows from a table completely, you use the DELETE statement. The following First, you specify the name of the table from which the rows are to be deleted in the FROM clause. As can be seen clearly in the output, we have 321 rows in total. 3) Delete some rows with a condition example. Below are the steps to delete rows based on the value (all Mid-West records): Select any cell in the data set from which you want to delete the rows. Click on the Data tab. In the ‘Sort & Filter’ group, click on the Filter icon. This will apply filters to all the headers cells in the dataset.
In base R you could do this...
df[ave(as.numeric(as.factor(df$a)), #convert a to numbers (factor levels) (required by ave) df$b, #group by b FUN=length) < 3, ] #return whether no of a's per b is less than 3 a b 1 name1 car 3 name1 bus 4 name2 train 6 name2 tour
5 Data transformation, You might also have noticed the row of three (or four) letter abbreviations under the from operating on the entire dataset to operating on it group-by-group. to find flights that weren't delayed (on arrival or departure) by more than two hours, Filter to remove noisy points and Honolulu airport, which is almost twice as far � Click the drop-down arrow in the column you will delete rows based on, then click Number Filters > Greater Than or Less Than as below screenshot: 3. In the Custom AutoFilter dialog box, enter the certain number after the is greater than or is less than box, and then click the OK button.
library(data.table) setDT(df)[, count := .N, by = b] ## convert df to data.table & create a column to count groups df <- df[!(count >= 3), ] ## delete rows that have count equal to 3 or more than 3 df[, count := NULL] ## delete the column created df a b 1: name1 car 2: name1 bus 3: name2 train 4: name2 tour
Comparing data frames, Joining the data frames; Finding duplicated rows; Finding unique rows or more data frames and find rows that appear in more than one data frame, or rows that Suppose you have the following three data frames, and you want to know whether each row from Find the rows which have duplicates in a different group. To remove one or more rows from a table completely, you use the DELETE statement. The following illustrates its syntax: DELETE [ TOP (expression) [ PERCENT ] ] FROM table_name [ WHERE search_condition]; First, you specify the name of the table from which the rows are to be deleted in the FROM clause.
Using Base R:
df <- data.frame(a = c("name1","name1","name1","name2","name2","name2","name3"), b=c("car","bike","bus","train","bike","tour","bike")) df lst <- table(df$b) df[df$b != names(lst)[lst >=3],] # a b # 1 name1 car # 3 name1 bus # 4 name2 train # 6 name2 tour
SQL query to delete duplicate rows, Then delete all the data from duplicate rows table then insert all data from There are two methods here to delete duplicates they are using "group by" and " Rank()" Query to delete 3 duplicated rows (in our example table) or repeated more� While performing data analysis, quite often we require to filter the data to remove unnecessary rows or columns. We have already discussed earlier how to drop rows or columns based on their labels . However, in this post we are going to discuss several approaches on how to drop rows from the dataframe based on certain condition applied on a column.
Data Wrangling Part 3: Basic and more advanced ways to filter rows, Apart from the basics of filtering, it covers some more nifty ways to If you want to select a specific group of animals for instance you can use the == comparison operator: sleep_total) %>% filter(!order %in% remove) ## # A tibble: 37 x 3 So imagine I want to find out all data rows where we NA in the first� Here are the simple steps to delete rows in excel based on cell value as follows: First Open Find & Replac e Dialog; In Replace Tab, make all those cells containing NULL values with Blank; Press F5 and select the blank option; The Right Click on active Sheet and select delete rows. It will delete all those rows based on cell value of containing word NULL. 3.
Solved: Remove rows with one or more empty values using JSL , Here is an example deleting all rows with missing cells in columns 2, 3 & 4: keeprows = Loc Found the output of V Sum() would return 0 for all null. To make� It will delete the all rows for which column ‘Age’ has value 30. Delete rows based on multiple conditions on a column. Suppose Contents of dataframe object dfObj is, Original DataFrame pointed by dfObj. Let’s delete all rows for which column ‘Age’ has value between 30 to 40 i.e.
Basic Statistical Analysis Using the R Statistical Package, As with any software program, there usually is more than one way to do things through R. Data are arranged with variables as columns and subjects as rows. Section 1.3.3 below discusses accessing individual variables within a data set. finds the mean of the variable 'agewalk' for those subjects with group equal to 1 . If you want to remove more than one row or column, select a cell in each row or column you want to delete. Under Table Tools , click Layout , and then click either Delete Row or Delete Column . The other quick way to delete rows and columns is to select the contents of a cell in a row or column you want to delete.