Read a CSV with PandasSpoiler (hover to show) import csv import pandas data = [] with open("weather_data.csv", "r") as file: data = file.readlines() csv_data = [] with open("weather_data.csv", "r") as file: data = csv.reader(file) for row in data: print(row) temperatures = [] for row in data: temperatures.append(temp[1]) print(temperatures) pandas_data = pandas.read_csv("weather_data.csv") print(pandas_data) print(pandas_data["temp"]) pd_to_dict = pandas_data.to_dict() print(pd_to_dict) print(pandas_data["temp"].to_list())
#ChallengeSpoiler (hover to show) #challenge avg = sum(pandas_data["temp"].to_list()) / len(pandas_data["temp"].to_list()) print(avg) print(pandas_data["temp"].mean())
#ChallengeSpoiler (hover to show) #challlenge print(pandas_data["temp"].max()) print(pandas_data["condition"]) print(pandas_data.condition) print(pandas_data[pandas_data.day == "Monday"])
#ChallengeSpoiler (hover to show) #challenge print(pandas_data[pandas_data.temp == pandas_data.temp.max()]) monday = pandas_data[pandas_data.day == "Monday"] print(monday.condition)
#ChallengeSpoiler (hover to show) #challenge print(int(monday.temp) * (9/5) + 32) data_dict = { "students": ["Amy", "James", "Angela"], "scores": [76, 56, 85] } scratch_data = pandas.DataFrame(data_dict) scratch_data.to_csv("scratch_data.csv")
#ChallengeSpoiler (hover to show) #challenge squirrel_data = pandas.read_csv("2018_Central_Park_Squirrel_Census_-_Squirrel_Data.csv") grey_squirrels = squirrel_data[squirrel_data["Primary Fur Color"] == "Gray"] red_squirrels = squirrel_data[squirrel_data["Primary Fur Color"] == "Cinnamon"] black_squirrels = squirrel_data[squirrel_data["Primary Fur Color"] == "Black"] grey_count = len(grey_squirrels["Primary Fur Color"].to_list()) red_count = len(red_squirrels["Primary Fur Color"].to_list()) black_count = len(black_squirrels["Primary Fur Color"].to_list()) squirrel_dict = { "Fur Count": ["grey", "red", "black"], "Count": [grey_count, red_count, black_count] } squirrel_dataFrames = pandas.DataFrame(squirrel_dict) squirrel_dataFrames.to_csv("squirrel_data.csv")
#ProjectSpoiler (hover to show) import turtle screen = turtle.Screen() screen.title("U.S. States Game") image = "blank_states_img.gif" screen.addshape(image) turtle.shape(image) #def get_mouse_click_coord(x, y): # print(x, y) #turtle.onscreenclick(get_mouse_click_coord) # Don't need screen.exitonclick() if you have this #turtle.mainloop() state_data = pandas.read_csv("50_states.csv") states = state_data.state.to_list() guessed_states = [] while len(guessed_states) < 50: guessed = len(guessed_states) answer_state = screen.textinput(str(guessed) + "/50 States Guessed Correct", "What's the another state's name?").title() if answer_state == "Exit": break state = state_data[state_data.state == answer_state] if answer_state in states: if answer_state not in guessed_states: guessed_states.append(answer_state) t = turtle.Turtle() t.hideturtle() t.penup() state = state_data[state_data.state == answer_state] print(state) x = state.x y = state.y t.goto(int(x), int(y)) t.write(state.state.item()) screen.exitonclick() missing_states = [] for missing_state in states: if missing_state not in guessed_states: missing_states.append(missing_state) missing_csv = pandas.DataFrame(missing_states) missing_csv.to_csv("states_to_learn.csv")