Code to filter out problematic 0 and NA entries

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Total newbie here, I totally apologize if/when at any point I sound like a complete idiot.

I am working in RStudio. I have imported a data file from excel. It has several columns with health information such as age, blood pressure, BMI, and a couple others. I need to remove the entries with 0s in a couple of the columns (you can't have 0 BMI or blood pressure) I also need to remove all of the entries with NAs.

I am stuck on what to do. I have tried the na.omit function, but afterwords I try doing things like mean() median() and it gives me the message "argument is not numeric or logical: returning NA" which makes no sense. I thought the NAs were supposed to be removed.

Please help. I need help cleaning this data.

Usually it's not good to remove the NA's because it may be NA for one column, but not the other, so you may exclude the wrong thing.

With the stats library, you can use the complete.cases(df) to remove all NA.

To change 0's to NA, you can do:

df[ df == 0] <- NA

Also if you want to ignore NA's while doing calculations you can do

median(df$col,na.rm = TRUE)

This will remove the NA from the calculations and you won't get NA as an output.

Data Cleaning with R and the Tidyverse: Detecting Missing Values, We just used the filter function to quickly filter out rows with a Churn Chaining functions together vertically makes our code extremely readable. When we run the is.na function, R recognizes both types of missing values. If a value is undefined, such as 0/0, “NaN” is the appropriate way to represent this  To add a filter on a column. Before you add a filter, choose icon to change to the list view. Choose the downwards arrow in the column heading, and then choose Filter. Do one of the following: Choose next to the box to select a value from a list. Enter filter criteria in the box. See the next section for details.

A tidyverse solution might look like this. Tidyverse is a set of packages developed by the R Studio team.

library(tidyverse)

data <- data %>%
  filter(BMI != 0, BloodPressure != 0, col != NA)

How do I remove not available data in R?, I use code "na.omit (data)" but the problem persists. Check if the data has infinite values (+Inf, -Inf; possibly coming form "log(0)" or something similar). How to filter/delete specific column values using R? should be able to delete all the rows with respective the column values which falls in the specified range using R  R doesn't know what you are doing in your analysis, so instead of potentially introducing bugs that would later end up being published an embarrassing you, it doesn't allow comparison operators to think NA is a value. improve this answer. edited May 23 '17 at 10:30. answered Mar 4 '15 at 15:33. 34 silver badges. 76 bronze badges.

First of all, you have to make sure that the columns you are interested in are numeric not character because direct import from excel files could produce unexpected column types. To do so use the function class(data_name$column_name).

Character variables cannot be handled with mean() and median() so you have to convert them first to numeric using

data_name$column_name <- as.numeric(data_name$column_name)

After that you can replace zeros with NA using ifelse function:

data_name$column_name <- ifelse(data_name$column_name == 0, NA, data_name$column_name)

Then, you can compute the mean and median in the normal way using the argument na.rm to remove missing values (NA):

mean_BMI <- mean(data_name$BMI, na.rm = TRUE)

12 Tidy data, Since table2 has separate rows for cases and population we needed to generate a Before creating the plot with change in cases over time, we need to filter table to only The code fails because the column names 1999 and 2000 are not non-​syntactic variable names. What's the difference between an NA and zero? For example, if the column is filled with arbitrary words not known beforehand, I want to make sure a specific word is not there. If a column was filled with names of fruits, I would want to take out "apple" without having to know the name of every other fruit in there. I would have to select every fruit but "apple" to filter "apple" out.

filter: Return rows with matching conditions in dplyr: A Grammar of , Use filter() to choose rows/cases where conditions are true. Unlike base subsetting with [, rows where the condition evaluates to NA are dropped. Sometimes it's more efficient to filter out values because there are fewer excluded items than included. Unfortunately, this functionality is not as straightforward as it should be in VBA. The only way I know to filter out values with VBA is to use Excel's spreadsheet-based Advanced Filter functionality.

dplyr can't summarize this variable · Issue #2919 · tidyverse/dplyr , I'm working with a data.frame and dplyr returns NA for all summaries for this Sorry for the zip file, github won't let me upload the file directly. test2.zip and the R code. your question, you can simply omit the NA variables with a filter : out all potentially problematic entries summarise(m = mean(russia))  Code to filter out problematic 0 and NA entries. I need to remove the entries with 0s in a couple of the columns (you can't have 0 BMI or blood pressure) I also

filter not retaining rows with NA values · Issue #3196 · tidyverse/dplyr , While it is not hard to add to the condition to keep those rows, it does mean you almost always have to write explicit code as absence of NA  Go to the worksheet that you want to auto refresh filter when data changes. 2. Right click the sheet tab, and select View Code from the context menu, in the popped out Microsoft Visual Basic for Applications window, please copy and paste the following code into the blank Module window, see screenshot: VBA code: Auto reapply filter when data

Comments
  • Please see this post stackoverflow.com/questions/5963269/…
  • Here is a great resource for starting with R . r4ds.had.co.nz/index.html. As per the guidelines for posting, please include sample code of how far you were able to get.
  • In case a row has BMI == 0 but blood_pressure != 0 ( or viceversa), or BMI == NA but blood_pressure != NA (or viceversa) are you going to remove it?