Question: Subset the data based on age, sex, or race. Are there any missing values in the data? Which strategy should you use to handle the
Subset the data based on age, sex, or race. Are there any missing values in the data? Which strategy should you use to handle the missing values? Consider if any new variables can be created using the existing variables. Explore the opportunities of transforming numeric variables through binning and transforming categorical variables by creating dummy variables.
| Urban | Siblings | White | Christian | FamilySize | Height | Weight | Income |
| 1 | 8 | 1 | 1 | 5 | 62 | 120 | 0 |
| 1 | 1 | 1 | 1 | 4 | 64 | 200 | 40000 |
| 1 | 1 | 1 | 1 | 3 | 65 | 131 | 25000 |
| 0 | 7 | 1 | 0 | 3 | 65 | 179 | 27400 |
| 1 | 4 | 1 | 1 | 6 | 66 | 145 | 52000 |
| 1 | 1 | 1 | 1 | 3 | 71 | 155 | 55000 |
| 1 | 2 | 1 | 1 | 5 | 71 | 180 | 60000 |
| 1 | 2 | 1 | 1 | 5 | 67 | 135 | 48000 |
| 1 | 1 | 1 | 1 | 4 | 73 | 185 | 0 |
| 0 | 3 | 1 | 1 | 4 | 63 | 130 | 38000 |
| 1 | 2 | 1 | 0 | 2 | 69 | 160 | 48000 |
| 1 | 2 | 1 | 0 | 1 | 69 | 155 | 120000 |
| 1 | 2 | 1 | 1 | 5 | 120 | 52000 | |
| 1 | 2 | 1 | 1 | 5 | 62 | 133 | 82000 |
| 1 | 1 | 1 | 1 | 4 | 64 | 110 | 36000 |
| 1 | 1 | 1 | 0 | 3 | 67 | 125 | 20000 |
| 1 | 1 | 1 | 1 | 4 | 63 | 123 | |
| 1 | 1 | 1 | 0 | 4 | 65 | 114 | 24000 |
| 1 | 1 | 1 | 0 | 4 | 67 | 146 | 50000 |
| 1 | 1 | 1 | 0 | 4 | 64 | 147 | 0 |
| 1 | 2 | 0 | 1 | 4 | 68 | 150 | 26000 |
| 1 | 5 | 1 | 0 | 4 | 70 | 185 | 35000 |
| 0 | 3 | 1 | 1 | 5 | 72 | 225 | 0 |
| 1 | 4 | 1 | 1 | 4 | 67 | 124 | 13000 |
| 1 | 4 | 1 | 1 | 4 | 64 | 108 | 44000 |
| 1 | 1 | 1 | 4 | 71 | 170 | 57000 | |
| 1 | 2 | 1 | 1 | 3 | 67 | 175 | 0 |
| 1 | 3 | 1 | 1 | 3 | 74 | 230 | 115000 |
| 1 | 1 | 0 | 1 | 4 | 71 | 210 | 50000 |
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