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"]
