In [2]:

    

import matplotlib.pyplot as plt
from matplotlib.dates import DateFormatter
import pandas as pd
import numpy as np


    

In [3]:

    

unrate = pd.read_csv('unrate.csv')
unrate['DATE'] = pd.to_datetime(unrate['DATE'])

dates = unrate['DATE']
unrate_vals = unrate['VALUE']

plt.plot(dates[0:12], unrate_vals[0:12])
locs, labels = plt.xticks(rotation=90)
print(locs)
step = (locs[1] - locs[0])/2
locs = np.arange(locs[0]-step, locs[len(locs)-1], step)
plt.xticks(locs,dates[0:12],rotation=50)
myFmt = DateFormatter("%y%m%d")
plt.gca().xaxis.set_major_formatter(myFmt)
plt.xlabel('Month')
plt.ylabel('Unemployment Rate')

plt.show()


    

    




[ 711158.  711218.  711279.  711340.  711401.  711462.]






    

In [7]:

    

fig = plt.figure(figsize=(12,12))
start = 12
for i in range(0,5):
    ax = fig.add_subplot(5,1,i+1)
    boundary = start * (i+1)
    ax.plot(unrate['DATE'][boundary-12:boundary], unrate['VALUE'][boundary-12:boundary])
    
plt.show()


    

In [8]:

    

unrate['MONTH'] = unrate['DATE'].dt.month


fig = plt.figure(figsize=(6,3))

plt.plot(unrate['MONTH'][0:12], unrate['VALUE'][0:12], c='red')
plt.plot(unrate['MONTH'][12:24], unrate['VALUE'][12:24], c='blue')
plt.show()


    

In [19]:

    

fig = plt.figure(figsize=(10,6))
start = 12
colors =['red', 'blue', 'green', 'orange', 'black']
labels = ['1948', '1949', '1950', '1951', '1952']
for i in range(0,5):
    higher_boundary = start*(i+1)
    lower_boundary = higher_boundary - start
    subset = unrate[lower_boundary:higher_boundary]
    plt.plot(subset['MONTH'], subset['VALUE'], c=colors[i], label=labels[i])
    plt.legend(loc='upper left')
    
plt.title("Monthly Unemployment Trends, 1948-1952")
plt.xlabel('Month, Integer')
plt.ylabel('Unemployment rate, Percent')
plt.show()


    

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