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Lab 1 255
karan221997 Feb 13, 2021
1ac50b9
final lab submission
karan221997 Feb 14, 2021
54c345a
Lab 2 submission
karan221997 Mar 13, 2021
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115 changes: 115 additions & 0 deletions lab1/Lab1_Output.txt
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Question 1:- # Load data from data/chipotle.tsv file using Pandas library and
# assign the dataset to the 'chipo' variable.
Answer:-
order_id ... item_price
0 1 ... $2.39
1 1 ... $3.39
2 1 ... $3.39
3 1 ... $2.39
4 2 ... $16.98
... ... ... ...
4617 1833 ... $11.75
4618 1833 ... $11.75
4619 1834 ... $11.25
4620 1834 ... $8.75
4621 1834 ... $8.75

[4622 rows x 5 columns]

Question 2:- # Top x number of entries from the dataset and display as markdown format.
Answer:- Also answer is in output.md file for this question

| | order_id | quantity | item_name | choice_description | item_price |
|---:|-----------:|-----------:|:--------------------------------------|:-------------------------------------------------------------------------------------------------------------------|:-------------|
| 0 | 1 | 1 | Chips and Fresh Tomato Salsa | nan | $2.39 |
| 1 | 1 | 1 | Izze | [Clementine] | $3.39 |
| 2 | 1 | 1 | Nantucket Nectar | [Apple] | $3.39 |
| 3 | 1 | 1 | Chips and Tomatillo-Green Chili Salsa | nan | $2.39 |
| 4 | 2 | 2 | Chicken Bowl | [Tomatillo-Red Chili Salsa (Hot), [Black Beans, Rice, Cheese, Sour Cream]] | $16.98 |
| 5 | 3 | 1 | Chicken Bowl | [Fresh Tomato Salsa (Mild), [Rice, Cheese, Sour Cream, Guacamole, Lettuce]] | $10.98 |
| 6 | 3 | 1 | Side of Chips | nan | $1.69 |
| 7 | 4 | 1 | Steak Burrito | [Tomatillo Red Chili Salsa, [Fajita Vegetables, Black Beans, Pinto Beans, Cheese, Sour Cream, Guacamole, Lettuce]] | $11.75 |
| 8 | 4 | 1 | Steak Soft Tacos | [Tomatillo Green Chili Salsa, [Pinto Beans, Cheese, Sour Cream, Lettuce]] | $9.25 |
| 9 | 5 | 1 | Steak Burrito | [Fresh Tomato Salsa, [Rice, Black Beans, Pinto Beans, Cheese, Sour Cream, Lettuce]] | $9.25 |

Question 3:- # The number of observations/entries in the dataset.
Answer:-
4622

Question 4:- # print data info.
Answer:-
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 4622 entries, 0 to 4621
Data columns (total 5 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 order_id 4622 non-null int64
1 quantity 4622 non-null int64
2 item_name 4622 non-null object
3 choice_description 3376 non-null object
4 item_price 4622 non-null object
dtypes: int64(2), object(3)
memory usage: 180.7+ KB
None

Question 5: # TODO return the number of columns in the dataset
Answer:-
5 true no exception

Question 6:- # TODO Print the name of all the columns.
Answer:-
order_id
quantity
item_name
choice_description
item_price

Question 7:- # print the most ordered item
Answer: assert item_name == 'Chicken Bowl'
assert order_id == 713926
assert quantity == 761 (Answer differs than the given because quantity was also taken in consideration)

Question 8:- # TODO How many items were orderd in total?
Answer:- 4972

Question 9:- # TODO
# 1. Create a lambda function to change all item prices to float.
# 2. Calculate total sales.
Answer:- 39237.02

Question 10:- # How many orders were made in the dataset?
Answer:- 1834

Question 11:- # TODO Average sales amount per order
Answer:- 21.39 error/exception

Question 12:- # TODO
# How many different items are sold?
Answer:- 50 no error/exception

Question 13: # TODO
# 1. convert the dictionary to a DataFrame
# 2. sort the values from the top to the least value and slice the first 5 items
# 3. create a 'bar' plot from the DataFrame
# 4. set the title and labels:
# x: Items
# y: Number of Orders
# title: Most popular items
# 5. show the plot. Hint: plt.show(block=True).
Answer:- Attached as image in file named as lab1_output.docx. Image name :- graph1.png

Question 14:- # TODO
# 1. create a list of prices by removing dollar sign and trailing space.
# 2. groupby the orders and sum it.
# group = self.chipo.groupby('order_id').agg({'float_item_price_list': ['sum']})
# print(group)
# 3. create a scatter plot:
# x: orders' item price
# y: orders' quantity
# s: 50
# c: blue
# 4. set the title and labels.
# title: Numer of items per order price
# x: Order Price
# y: Num Items
Answer:- Attached as image in file named as lab1_output.docx. Image name :- graph2.png
15 changes: 15 additions & 0 deletions lab1/Pipfile
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[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"

[packages]
pandas = "*"
numpy = "*"
tabulate = "==0.8.7"
matplotlib = "*"

[dev-packages]

[requires]
python_version = "3.9"
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