Answer Posted / Sumit Srivastava

In R, you can use the `is.na()` function to find missing values, and then use the `na.omit()` function to remove them. Here's an example: nn```rndata <- data.frame(a = c(1, 2, NA, 4), b = c(NA, 5, 6, 7))n# Find number of missing valuesnn_miss <- sum(is.na(data))nprint(n_miss)nn# Remove rows with missing valuesndata_clean <- na.omit(data)n```

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