diff --git a/README.md b/README.md
index 248d62c..ceb8eba 100644
--- a/README.md
+++ b/README.md
@@ -32,7 +32,7 @@ Use the data to complete the following tasks in `medical_data_visualizer.py`:
 * Normalize the data by making 0 always good and 1 always bad. If the value of `cholesterol` or `gluc` is 1, make the value 0. If the value is more than 1, make the value 1.
 * Convert the data into long format and create a chart that shows the value counts of the categorical features using seaborn's `catplot()`. The dataset should be split by 'Cardio' so there is one chart for each `cardio` value. The chart should look like `examples/Figure_1.png`.
 * Clean the data. Filter out the following patient segments that represent incorrect data:
-  - diastolic pressure is higher than systolic (Keep the correct data with `df['ap_lo'] <= df['ap_hi'])`)
+  - diastolic pressure is higher than systolic (Keep the correct data with `(df['ap_lo'] <= df['ap_hi'])`)
   - height is less than the 2.5th percentile (Keep the correct data with `(df['height'] >= df['height'].quantile(0.025))`)
   - height is more than the 97.5th percentile
   - weight is less than the 2.5th percentile