freecodecamp-data-analysis/medical-data-visualizer
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fix: add missing bracket in README (#8)

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Seth 2021-03-12 17:39:52 +01:00 committed by GitHub
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@ -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. * 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`. * 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: * 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 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 - height is more than the 97.5th percentile
- weight is less than the 2.5th percentile - weight is less than the 2.5th percentile