import seaborn as sns import pandas as pd import numpy as np from weather_data import london_data # Look at the first few rows of the dataset print(london_data.head()) # Look at rows 100-199 print(london_data.iloc[100:200]) # Take a look at how many datapoints there are print(len(london_data)) # Save the 'TemperatureC' column to a variable temp = london_data['TemperatureC'] # Find the average temperature in London in 2015 average_temp = np.mean(temp) # Calculate the variance of the temperature column temperature_var = np.var(temp) print(temperature_var) # Calculate the standard deviation of the tempeature column temperature_standard_deviation = np.std(temp) #print(temperature_standard_deviation) # Filter the temperature by the months June and July june = london_data.loc[london_data["month"] == 6]["TemperatureC"] july = london_data.loc[london_data["month"] == 7]["TemperatureC"]
""" import codecademylib3_seaborn import pandas as pd import numpy as np from weather_data import london_data print(london_data.iloc[100:200]) print(len(london_data)) temp = london_data["TemperatureC"] average_temp = np.mean(temp) temperature_var = np.var(temp) temperature_standard_deviation = np.std(temp) london_data.head() june = london_data.loc[london_data["month"] == 6]["TemperatureC"] july = london_data.loc[london_data["month"] == 7]["TemperatureC"] print(np.mean(june)) print(np.mean(july)) print(np.std(june)) print(np.std(july)) for i in range(1, 13): month = london_data.loc[london_data["month"] == i]["TemperatureC"] print("The mean temperature in month " + str(i) + " is " + str(np.mean(month)))
import codecademylib3_seaborn import pandas as pd import numpy as np from weather_data import london_data print(london_data.head(10)) print(len(london_data)) temp=london_data['TemperatureC'] average_temp=np.mean(temp) print(average_temp) temperature_var=np.var(temp) print(temperature_var) temp_std=np.std(temp) print(temp_std) #create june and july temp column june=london_data.loc[london_data['month']==6]['TemperatureC'] july=london_data.loc[london_data['month']==7]['TemperatureC'] print(np.mean(june)) print(np.mean(july)) print(np.std(june)) print(np.std(july)) for i in range(1, 13): month = london_data.loc[london_data["month"] == i]["TemperatureC"] print("The mean temperature in month "+str(i) +" is "+ str(np.mean(month))) print("The standard deviation of temperature in month "+str(i) +" is "+ str(np.std(month)) +"\n")
import codecademylib3_seaborn import pandas as pd import numpy as np from weather_data import london_data print(london_data.columns) print(london_data.head(40000)) temp = london_data['TemperatureC'] average_temp = round(np.mean(temp), 2) temperature_var = round(np.var(temp), 2) print(average_temp) print(temperature_var) temperature_standard_deviation = round(np.std(temp), 2) print('London StDev: ', temperature_standard_deviation) june = london_data.loc[london_data['month'] == 6]['TemperatureC'] july = london_data.loc[london_data['month'] == 7]['TemperatureC'] june_mean = np.mean(june) june_StDev = np.std(june) july_mean = np.mean(july) july_StDev = np.std(july) print('June mean:', round(june_mean, 2)) print('June StDev:', round(june_StDev, 2)) print('July mean:', round(july_mean, 2)) print('July StDev:', round(july_StDev, 2)) for i in range(1, 13): month = london_data.loc[london_data["month"] == i]["TemperatureC"]