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Merge pull request #6 from Rahullkumr/addition
Add: USA states guessing game
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‎Day25-Pandas-USAstatesGame/2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv‎

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‎Day25-Pandas-USAstatesGame/50_states.csv‎

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state,x,y
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Alabama,139,-77
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Alaska,-204,-170
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Arizona,-203,-40
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Arkansas,57,-53
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California,-297,13
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Colorado,-112,20
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Connecticut,297,96
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Delaware,275,42
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Florida,220,-145
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Georgia,182,-75
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Hawaii,-317,-143
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Idaho,-216,122
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Illinois,95,37
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Indiana,133,39
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Iowa,38,65
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Kansas,-17,5
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Kentucky,149,1
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Louisiana,59,-114
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Maine,319,164
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Maryland,288,27
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Massachusetts,312,112
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Michigan,148,101
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Minnesota,23,135
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Mississippi,94,-78
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Missouri,49,6
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Montana,-141,150
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Nebraska,-61,66
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Nevada,-257,56
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New Hampshire,302,127
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New Jersey,282,65
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New Mexico,-128,-43
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New York,236,104
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North Carolina,239,-22
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North Dakota,-44,158
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Ohio,176,52
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Oklahoma,-8,-41
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Oregon,-278,138
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Pennsylvania,238,72
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Rhode Island,318,94
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South Carolina,218,-51
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South Dakota,-44,109
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Tennessee,131,-34
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Texas,-38,-106
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Utah,-189,34
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Vermont,282,154
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Virginia,234,12
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Washington,-257,193
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West Virginia,200,20
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Wisconsin,83,113
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Wyoming,-134,90

‎Day25-Pandas-USAstatesGame/README.md‎

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# USA States Game
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This is an interactive Python game where users attempt to name all 50 U.S. states. The program will show an image of the United States and ask users to input state names. If a correct state name is entered, it will be displayed on the map. The game also generates a file with the names of any states the player missed.
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![](./USAstatesGame.png)
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## Features
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- Displays a map of the USA with a blank outline of the states.
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- Allows users to guess states' names and shows correct guesses on the map.
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- Generates a `states_you_missed.csv` file listing any states not guessed during the game.
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## Prerequisites
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1. **Python 3.x**: Ensure Python is installed. You can download it from [Python.org](https://www.python.org/).
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2. **Pandas**: Install the `pandas` library for data manipulation:
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```
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pip install pandas
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```
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3. **Turtle Graphics**: The `turtle` module is a standard Python library, so no additional installation is needed.
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## Project Structure
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- `main.py`: Main game file containing the code to run the game.
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- `50_states.csv`: CSV file with state names and their coordinates.
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- `blank_states_img.gif`: Image of the USA map outline used as the game background.
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## Getting Started
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1. **Clone the repository**: Clone the project to your local machine using Git.
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```
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git clone https://github.com/Rahullkumr/100daysofpython.git
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```
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2. **Navigate to the project directory**:
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```
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cd Day25-Pandas-USAstatesGame
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```
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3. **Ensure all required files are in the directory**:
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- `main.py`
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- `50_states.csv`
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- `blank_states_img.gif`
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## Running the Game
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To start the game, execute the following command:
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```
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python main.py
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```
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## How to Play
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1. When the game starts, a prompt will appear asking for a state name.
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2. Type the name of a state and press Enter.
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3. If the state name is correct, it will appear on the map at the state's location.
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4. Type "Exit" if you want to stop the game early.
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- When you exit, a `states_you_missed.csv` file will be created in the project directory, listing any states you did not guess.
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## Note
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- Ensure that `blank_states_img.gif` is present in the same directory as the code. If it's missing, the game will not display the background map.
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## Author
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- Created by [Rahul Kumar](https://github.com/rahullkumr)
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Enjoy learning and challenging yourself with this USA states guessing game!

‎Day25-Pandas-USAstatesGame/USAstatesGame.png‎

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‎Day25-Pandas-USAstatesGame/blank_states_img.gif‎

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‎Day25-Pandas-USAstatesGame/data_analysis_basics.py‎

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""" BASICS OF DATA ANALYSIS """
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# with open('./weather_data.csv', 'r') as file:
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# data = file.readlines()
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# print(data)
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"""There is a lot of headache in cleaning the above data, so try other way (see below)"""
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# import csv
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# with open('./weather_data.csv') as data_file:
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# data = csv.reader(data_file)
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# temperatures = []
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# for row in data:
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# if row[1] != 'temp':
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# temperatures.append(int(row[1]))
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#
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# print(temperatures)
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"""
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A lot of lines of code is written just to get one column, what if there are 100s of columns and complex data,
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so it is not a convenient way. Now let's use PANDAS library and see the magic.
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"""
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import pandas as pd
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data = pd.read_csv('./weather_data.csv')
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print(data['temp'])
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# DataFrame: whole table of Excel sheet or google sheet (2D)
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# eg: data
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# Series: a column of Excel sheet or google sheet (1D)
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# eg: data['temp']
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data_as_dict = data.to_dict()
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temp_list = data['temp'].to_list()
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print(data_as_dict)
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print(temp_list)
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print('Average Temperature: ', sum(temp_list)/len(temp_list))
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print('Average temp using series: ', data['temp'].mean())
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print('Max temp using series: ', data['temp'].max()) # data['temp'] == data.temp
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print('Max temp using series: ', data.temp.max())
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print(data.condition)
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# Get data in row
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print(data[data.day == 'Monday']) # its dataframe
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# Get the row which has maximum temperature
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print(data[data.temp == data.temp.max()]) # its dataframe
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# Get Monday's condition
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print(data[data.day == "Monday"].condition)
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# challenge: show Monday's temperature in Fahrenheit ((0°C × 9/5) + 32 = 32°F)
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monday_temp = data.temp[0]
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print(monday_temp)
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print("Monday's temp in Fahrenheit: ", monday_temp * 9/5 + 32, "°F")
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# create a DataFrame from scratch
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data_dict = {
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"names": ['Amit', 'Rohit', 'Sumit'],
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"score": [45, 73, 66]
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}
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df_from_scratch = pd.DataFrame(data_dict)
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print(df_from_scratch)
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# save the DataFrame in csv format
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df_from_scratch.to_csv('./students_data.csv') # path where you want to save

‎Day25-Pandas-USAstatesGame/main.py‎

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import turtle
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import pandas as pd
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screen = turtle.Screen()
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screen.title('USA states game')
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image = 'blank_states_img.gif'
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screen.addshape(image)
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turtle.shape(image)
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data = pd.read_csv('./50_states.csv')
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all_states = data.state.to_list()
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guessed_states = []
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while len(guessed_states) < 50:
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ans_state = (turtle.textinput(title=f'{len(guessed_states)}/50 States Correct',
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prompt="What's another state's name? ")).title()
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if ans_state == 'Exit':
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# states_you_missed.csv
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missed_states_dict = {
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"Missed States": [state for state in all_states if state not in guessed_states]
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}
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df = pd.DataFrame(missed_states_dict)
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df.to_csv('./states_you_missed.csv', mode='w')
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break
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if ans_state in all_states:
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guessed_states.append(ans_state)
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t = turtle.Turtle()
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t.hideturtle()
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t.penup()
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state_data = data[data['state'] == ans_state]
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t.goto(state_data.x.item(), state_data.y.item())
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t.write(ans_state)
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‎Day25-Pandas-USAstatesGame/squirrel.py‎

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# Importing the pandas library, commonly used for data manipulation and analysis
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import pandas as pd
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# Reading the CSV file into a DataFrame
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data = pd.read_csv('./2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv')
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'''
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# ============== This is my way ===========================
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pfc = data['Primary Fur Color']
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fur_color_dict = {
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"Fur Color": ['Gray', 'Cinnamon', 'Black'],
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"Count": []
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}
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g_count, b_count, c_count = 0, 0, 0
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for i in pfc:
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if i in ('Gray', 'Cinnamon', 'Black'):
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g_count += 1 if i == "Gray" else 0
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c_count += 1 if i == "Cinnamon" else 0
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b_count += 1 if i == "Black" else 0
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fur_color_dict["Count"] = [g_count, c_count, b_count]
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print(fur_color_dict)
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'''
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# Better way
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pfc = data['Primary Fur Color']
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grey_squirrel_count = len(data[data['Primary Fur Color'] == 'Gray'])
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cinnamon_squirrel_count = len(data[data['Primary Fur Color'] == 'Cinnamon'])
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black_squirrel_count = len(data[data['Primary Fur Color'] == 'Black'])
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fur_color_dict = {
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"Fur Color": ['Gray', 'Cinnamon', 'Black'],
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"Count": [grey_squirrel_count, cinnamon_squirrel_count, black_squirrel_count]
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}
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# Creating and printing the DataFrame
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df = pd.DataFrame(fur_color_dict)
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print(df)
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# Saving the DataFrame as a new CSV file with squirrel fur color counts
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df.to_csv('./squirrel_count.csv')

‎Day25-Pandas-USAstatesGame/squirrel_count.csv‎

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,Fur Color,Count
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0,Gray,2473
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1,Cinnamon,392
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2,Black,103

‎Day25-Pandas-USAstatesGame/states_you_missed.csv‎

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,Missed States
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0,Arizona
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1,Arkansas
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2,Colorado
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3,Connecticut
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4,Delaware
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5,Florida
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6,Georgia
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7,Hawaii
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8,Idaho
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9,Illinois
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10,Indiana
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11,Iowa
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12,Kansas
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13,Kentucky
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14,Louisiana
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15,Maine
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16,Maryland
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17,Massachusetts
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18,Michigan
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19,Minnesota
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20,Mississippi
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21,Missouri
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22,Montana
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23,Nebraska
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24,Nevada
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25,New Hampshire
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26,New Jersey
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27,New Mexico
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28,New York
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29,North Carolina
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30,North Dakota
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31,Oklahoma
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32,Oregon
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33,Pennsylvania
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34,Rhode Island
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35,South Carolina
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36,South Dakota
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37,Tennessee
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38,Texas
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39,Utah
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40,Vermont
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41,Virginia
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42,West Virginia
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43,Wisconsin
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44,Wyoming

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