import pandas as pd
import matplotlib.pyplot as plt

# turn on print for all rows
pd.set_option('display.max_rows', None)
us_data = 'US-Data.csv'
uk_data = 'UK-Data.csv'

master_us_df = pd.read_csv(us_data)
master_uk_df = pd.read_csv(uk_data)

column_filter = ['Age','Centimeters']

us_male_filter = master_us_df['Gender'] == 'male'
filtered_us_male_data = master_us_df.loc[us_male_filter,column_filter]
grouped_us_male_data = filtered_us_male_data.groupby(['Age']).mean()

uk_male_filter = master_uk_df['Gender'] == 'male'
filtered_uk_male_data = master_uk_df.loc[uk_male_filter,column_filter]
grouped_uk_male_data = filtered_uk_male_data.groupby(['Age']).mean()

us_female_filter = master_us_df['Gender'] == 'female'
filtered_us_female_data = master_us_df.loc[us_female_filter,column_filter]
grouped_us_female_data = filtered_us_female_data.groupby(['Age']).mean()

uk_female_filter = master_uk_df['Gender'] == 'female'
filtered_uk_female_data = master_uk_df.loc[uk_female_filter,column_filter]
grouped_uk_female_data = filtered_uk_female_data.groupby(['Age']).mean()


master_us_data = None
filtered_us_male_data = None
filtered_us_female_data = None

master_uk_data = None
filtered_uk_male_data = None
filtered_uk_female_data = None

axes = plt.axes()

plt.plot(grouped_us_male_data.index,grouped_us_male_data['Centimeters'], color='blue', label="US Male")
plt.plot(grouped_us_female_data.index,grouped_us_female_data['Centimeters'], color='green', label="US Female")

plt.plot(grouped_uk_male_data.index,grouped_uk_male_data['Centimeters'], color='red', label="UK Male")
plt.plot(grouped_uk_female_data.index,grouped_uk_female_data['Centimeters'], color='black', label="UK Female")

plt.title("Height vs Age for US/UK Records")
plt.xlabel("Age")
plt.ylabel("Height (in Centimeters)")

axes.legend(loc='best', frameon=False)

plt.grid()
plt.show()