id gpa gender breakfast calories_chicken calories_day calories_scone coffee
1 1 2.4 2 1 430 NaN 315 1
2 2 3.654 1 1 610 3 420 2
3 3 3.3 1 1 720 4 420 2
4 4 3.2 1 1 430 3 420 2
5 5 3.5 1 1 720 2 420 2
6 6 2.25 1 1 610 3 980 2
comfort_food
1 none
2 chocolate, chips, ice cream
3 frozen yogurt, pizza, fast food
4 Pizza, Mac and cheese, ice cream
5 Ice cream, chocolate, chips
6 Candy, brownies and soda.
comfort_food_reasons
1 we dont have comfort
2 Stress, bored, anger
3 stress, sadness
4 Boredom
5 Stress, boredom, cravings
6 None, i don't eat comfort food. I just eat when i'm hungry.
comfort_food_reasons_coded cook comfort_food_reasons_coded_1 cuisine
1 9 2 9 NaN
2 1 3 1 1
3 1 1 1 3
4 2 2 2 2
5 1 1 1 2
6 4 3 4 NaN
diet_current
1 eat good and exercise
2 I eat about three times a day with some snacks. I try to eat healthy but it doesn't always work out that- sometimes eat fast food and mainly eat at Laker/ Egan
3 toast and fruit for breakfast, salad for lunch, usually grilled chicken and veggies (or some variation) for dinner
4 College diet, cheap and easy foods most nights. Weekends traditionally, cook better homemade meals
5 I try to eat healthy but often struggle because of living on campus. I still try to keep the choices I do make balanced with fruits and vegetables and limit the sweats.
6 My current diet is terrible. I barely have time to eat a meal in a day. When i do eat it's mostly not healthy.
diet_current_coded drink
1 1 1
2 2 2
3 3 1
4 2 2
5 2 2
6 2 2
eating_changes
1 eat faster
2 I eat out more than usual.
3 sometimes choosing to eat fast food instead of cooking simply for convenience
4 Accepting cheap and premade/store bought foods
5 I have eaten generally the same foods but I do find myself eating the same food frequently due to what I have found I like from egan and the laker.
6 Eating rice everyday. Eating less homemade food.
eating_changes_coded eating_changes_coded1 eating_out employment ethnic_food
1 1 1 3 3 1
2 1 2 2 2 4
3 1 3 2 3 5
4 1 3 2 3 5
5 3 4 2 2 4
6 1 3 1 3 4
exercise father_education father_profession fav_cuisine fav_cuisine_coded
1 1 5 profesor Arabic cuisine 3
2 1 2 Self employed Italian 1
3 2 2 owns business italian 1
4 3 2 Mechanic Turkish 3
5 1 4 IT Italian 1
6 2 1 Taxi Driver African 6
fav_food food_childhood fries fruit_day
1 1 rice and chicken 2 5
2 1 chicken and biscuits, beef soup, baked beans 1 4
3 3 mac and cheese, pizza, tacos 1 5
4 1 Beef stroganoff, tacos, pizza 2 4
5 3 Pasta, chicken tender, pizza 1 4
6 3 Fries, plaintain & fried fish 1 2
grade_level greek_food healthy_feeling
1 2 5 2
2 4 4 5
3 3 5 6
4 4 5 7
5 4 4 6
6 2 2 4
healthy_meal
1 looks not oily
2 Grains, Veggies, (more of grains and veggies), small protein and fruit with dairy
3 usually includes natural ingredients; nonprocessed food
4 Fresh fruits& vegetables, organic meats
5 A lean protein such as grilled chicken, green vegetables and brown rice or other whole grain
6 Requires veggies, fruits and a cooked meal.
ideal_diet
1 being healthy
2 Try to eat 5-6 small meals a day. While trying to properly distribute carbs, protein, fruits, veggies, and dairy.
3 i would say my ideal diet is my current diet
4 Healthy, fresh veggies/fruits & organic foods
5 Ideally I would like to be able to eat healthier foods in order to loose weight.
6 My ideal diet is to eat 3 times a day including breakfast on time. Eat healthy food.
ideal_diet_coded income indian_food italian_food life_rewarding
1 8 5 5 5 1
2 3 4 4 4 1
3 6 6 5 5 7
4 2 6 5 5 2
5 2 6 2 5 1
6 2 1 5 5 4
marital_status
1 1
2 2
3 2
4 2
5 1
6 2
meals_dinner_friend
1 rice, chicken, soup
2 Pasta, steak, chicken
3 chicken and rice with veggies, pasta, some kind of healthy recipe
4 Grilled chicken \nStuffed Shells\nHomemade Chili
5 Chicken Parmesan, Pulled Pork, Spaghetti and meatballs
6 Anything they'd want. I'd ask them before hand what they want to eat and it depends on which type of friend is coming.
mother_education mother_profession nutritional_check on_off_campus
1 1 unemployed 5 1
2 4 Nurse RN 4 1
3 2 owns business 4 2
4 4 Special Education Teacher 2 1
5 5 Substance Abuse Conselor 3 1
6 1 Hair Braider 1 1
parents_cook pay_meal_out persian_food self_perception_weight soup sports
1 1 2 5 3 1 1
2 1 4 4 3 1 1
3 1 3 5 6 1 2
4 1 2 5 5 1 2
5 1 4 2 4 1 1
6 2 5 5 5 1 2
thai_food tortilla_calories turkey_calories type_sports veggies_day vitamins
1 1 1165 345 car racing 5 1
2 2 725 690 Basketball 4 2
3 5 1165 500 none 5 1
4 5 725 690 nan 3 1
5 4 940 500 Softball 4 2
6 4 940 345 None. 1 2
waffle_calories weight
1 1315 187
2 900 155
3 900 I'm not answering this.
4 1315 Not sure, 240
5 760 190
6 1315 190
id gender calories_chicken calories_scone tortilla_calories turkey_calories
1 1 M 430 315 1165 345
2 2 F 610 420 725 690
3 3 F 720 420 1165 500
4 4 F 430 420 725 690
5 5 F 720 420 940 500
6 6 F 610 980 940 345
waffle_calories
1 1315
2 900
3 900
4 1315
5 760
6 1315
dim(new_data)
[1] 125 7
There are 125 rows and 7 columns.
The data was reshaped from wide to long format, and missing values in the selected variables were removed. I have removed the missing values from the relevant columns. The removal of these missing values will not affect subsequent aggregation, visualization, and analysis.
Waffles have the highest calorie count at 1073.4 calories, with a median of 900 and a maximum of 1315. Tortillas rank second highest at 947.6 calories. Scones have the lowest average calorie count at 505.2 calories.
Although turkey and chicken are different poultry types, the differences in metrics derived from this data are not significant.
I plan to divide participants into male and female groups to examine whether there are differences in food calorie intake between genders.
# A tibble: 10 × 5
gender food_item Gmean_calories Gmedian_calories n
<chr> <chr> <dbl> <dbl> <int>
1 F chicken 588. 610 76
2 F scone 476. 420 75
3 F tortilla 912. 940 75
4 F turkey 537. 500 76
5 F waffle 1044. 900 76
6 M chicken 561. 610 49
7 M scone 549. 420 49
8 M tortilla 1002. 940 49
9 M turkey 584. 500 49
10 M waffle 1119. 1315 49
Although the average calorie intake was slightly higher among males, but the counts of females is more than males, resulting in an imbalance between the two groups. Therefore, this dataset does not support a clear conclusion about gender differences.
