Day 025

Udemy Python Bootcamp Day 025

CSV
CSVs are very common way of representing tabula data, so data that fits into tables like a spreadsheet.
And CSV, stands for Comma Separated Values.

There's actually a inbuilt library that helps us with CSVs because Python is a language that's used really heavily for data processing, data analysis. There's a lot of great tools for working with tabula data.

import csv

with open("weather_data.csv") as data_file:
    data = csv.reader(data_file)
    temperatures = []
    for row in data:
        if row[1] != "temp":
            temperatures.append(int(row[1]))
    print(temperatures)

#output
[12, 14, 15, 14, 21, 22, 24]

Pandas
Pandas is super helpful and super powerful to perform data analysis on tabula data.

documentation
https://pandas.pydata.org/docs/getting_started/index.html#getting-started

import pandas

data = pandas.read_csv("weather_data.csv")
print(data)

#output
day temp condition
0 Monday 12 Sunny
1 Tuesday 14 Rain
2 Wednesday 15 Rain
3 Thursday 14 Cloudy
4 Friday 21 Sunny
5 Saturday 22 Sunny
6 Sunday 24 Sunny

print(data["temp"])

#output
0 12
1 14
2 15
3 14
4 21
5 22
6 24
Name: temp, dtype: int64

Data Frame

import pandas

data = pandas.read_csv("weather_data.csv")
print(type(data))

#output
#<class 'pandas.core.frame.DataFrame'>

A dara frame is kind of the equivalent of whole table.
So every single sheet inside an Excel file or inside a Google sheet file would be considered a data frame in Pandas.
https://pandas.pydata.org/docs/reference/frame.html#serialization-io-conversion

Series

print(type(data["temp"]))

#output
#<class 'pandas.core.series.Series'>

THe series is the other super important concept in pandas.
And the Series is basically equivalent to a list. It's kind of like a single column in the table.
https://pandas.pydata.org/docs/reference/series.html#computations-descriptive-stats

Whole table is basically a data frame in pandas and every single column is a series kind of like a list in pandas.

import pandas

data = pandas.read_csv("weather_data.csv")

temp_list = data["temp"].to_list()
average = sum(temp_list) / len(temp_list)
print(average)

#output
17.428571428571427

series.mean()

print(data["temp"].mean())

#output
17.428571428571427

series.max()

print(data["temp"].max())

#output
24

---

print(data["condition"])
print(data.condition)

위 두줄의 값은 똑같음
#output
0 Sunny
1 Rain
2 Rain
3 Cloudy
4 Sunny
5 Sunny
6 Sunny
Name: condition, dtype: object

---

# Get data in Row
print(data[data.day == "Monday"])

#output
day temp condition
0 Monday 12 Sunny

---

print(data[data.temp == data.temp.max()])

#output
day temp condition
6 Sunday 24 Sunny

---

monday = data[data.day == "Monday"]
monday_temp = int(monday.temp)
monday_temp_F = monday_temp * 9/5 + 32
print(monday_temp_F)

#output
53.6

---

# Create a dataframe from scratch
data_dict = {
    "students": ["Amy", "James", "Angela"],
    "scores": [76, 56, 65]
}
data = pandas.DataFrame(data_dict)
print(data)

#output
students scores
0 Amy 76
1 James 56
2 Angela 65

---

data.to_csv("new_data.csv")

new_data.csv
,students,scores
0,Amy,76
1,James,56
2,Angela,65

---

Squirrel Count

import pandas

data = pandas.read_csv("2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv")
gray_squirrel_count = len(data[data["Primary Fur Color"] == "Gray"])
cinnamon_squirrel_count = len(data[data["Primary Fur Color"] == "Cinnamon"])
black_squirrel_count = len(data[data["Primary Fur Color"] == "Black"])

data_dict = {
    "Colours": ["Gray", "Cinnamon", "Black"],
    "Count": [gray_squirrel_count, cinnamon_squirrel_count, black_squirrel_count]
}
df = pandas.DataFrame(data_dict)
df.to_csv("squirrel_count.csv")

squirrel_count.csv
,Colours,Count
0,Gray,2473
1,Cinnamon,392
2,Black,103

US States Game

• Convert the guess to Title case
• Check if the guess is among the 50 states
• Write correct guesses onto the map
• Use a loopp to allow the user to keep guessing
• Record the correct guesses in a list
• Keep track of the score
  
  

turtle.onscreenclick()

def get_mouse_click_coor(x, y):
    print(x, y)

turtle.onscreenclick(get_mouse_click_coor)

turtle.mainloop()  # Which is keep our screen open

Final

import turtle
import pandas

screen = turtle.Screen()
screen.title("U.S. States Game")
image = "blank_states_img.gif"
screen.addshape(image)
turtle.shape(image)

data = pandas.read_csv("50_states.csv")
all_states = data.state.to_list()
guessed_states = []

while len(guessed_states) < 50:
    answer_state = screen.textinput(title=f"{len(guessed_states)}/50 States Correct",
                                    prompt="What's another state's name?").title()
    if answer_state == "Exit":
        missing_states = []
        for state in all_states:
            if state not in guessed_states:
                missing_states.append(state)
        new_data = pandas.DataFrame(missing_states)
        new_data.to_csv("states_to_learn.csv")
        break
    # If answer_state is one of the states in all the states of the 50_states.csv
        # If they got it right:
            # Create a turtle to write the name of the state at the state's x and y coordate
    if answer_state in all_states:
        guessed_states.append(answer_state)
        t = turtle.Turtle()
        t.hideturtle()
        t.penup()
        state_data = data[data.state == answer_state]
        t.goto(int(state_data.x), int(state_data.y))
        t.write(answer_state)  # t.write(state_data.state.item())