ADVDMLInClassWork1_2.py

# -*- coding: utf-8 -*-
"""
Created on Tue May 15 17:11:53 2018

@author: fengh
"""
# Section 1
# Q1
import pandas as pd
from io import StringIO

data1 = """
ID	Sales
1	7641
7	6621
6	8089
9	4719
7	2162
4	5235
2	2082
9	3887
5	4782
3	2576
8	6701
9	2154
8	3546
7	8648
5	9777
7	3143
7	2768
5	8518
1	8063
9	9086
5	8942"""
Qtr1 = pd.read_table(StringIO(data1), sep="\s+")
Qtr1.head(5)

data2 = """
ID	Sales
2	7668
7	7365
7	1837
5	1320
4	3674
2	9952
4	7874
9	4598
4	7393
5	5986
7	1120
2	2323
5	9756
3	7382
2	8156
1	8620
4	5689
5	6785
7	8425
1	1976
7	1858"""
Qtr2 = pd.read_table(StringIO(data2), sep="\s+")
Qtr2.head(5)
# Q2
# part a
sheet1 = """
1	4	X	9
2	3	W	5
3	2	W	7
4	4	X	7
5	3	W	5
6	5	CE	6
1	6	E	5
6	4	W	7
1	3	V	5
2	4	S	7
2	7	W	3
4	9	W	9
2	7	X	9
2	5	V	2
4	7	S	7
5	6	V	6
5	1	S	5
1	7	V	3
1	7	S	9
3	7	W	2
6	8	X	9
5	5	CE	8
6	5	CE	7
4	5	W	2
2	7	X	8
5	3	CE	3
2	2	S	5
1	4	V	2
2	1	CE	9
1	3	W	3
2	3	S	8
2	5	V	4"""
Sheet1 = pd.read_table(StringIO(sheet1), sep="\s+")
Sheet1 = pd.DataFrame(Sheet1, columns = ["Person", "Quantity", "Label", "Data"])
Sheet1.head(5)

# part b
# Dont' quite sure about this one
# Do you mean read from original file again?
# if so, what's the point to repeat same process as part a?
col3 = """
1	4	X
2	3	W
3	2	W
4	4	X
5	3	W
6	5	CE
1	6	E
6	4	W
1	3	V
2	4	S
2	7	W
4	9	W
2	7	X
2	5	V
4	7	S
5	6	V
5	1	S
1	7	V
1	7	S
3	7	W
6	8	X
5	5	CE
6	5	CE
4	5	W
2	7	X
5	3	CE
2	2	S
1	4	V
2	1	CE
1	3	W
2	3	S
2	5	V"""
Col3 = pd.read_table(StringIO(col3), sep="\s+")
Col3 = pd.DataFrame(Col3, columns = ["ID", "Quantity", "Total"])
Col3.head(5)

# part c
sheet2 = """
Flavor	Data
Choc	23
Van	12
Van	43
Choc	32
Van	43
Choc	91
Van	29
Choc	31
Choc	75
Choc	34"""
Sheet2 = pd.read_table(StringIO(sheet2), sep="\s+")
Sheet2['Price'] = 0
Sheet2.Price[Sheet2.Flavor == 'Choc'] = 2.00
Sheet2.Price[Sheet2.Flavor == 'Van'] = 1.50
Sheet2['Total'] = Sheet2['Price'] * Sheet2['Data']
Sheet2 = Sheet2.drop(columns='Price')
print(Sheet2.head(5))


# Q3
# part a
import os

os.chdir("C:\\Users\\fengh\\Desktop\\CurrentData")
os.getcwd()

# part b
os.listdir("C:\\Users\\fengh\\Desktop\\CurrentData")

# part c
# first I don't understand what do you mean by upload the file to python environment
# second, what do you mean by not use full path
# since I have the file under my current folder
# there is no reason to use full path then
# I will just read this .tsv file and make it a Dataframe for this part
# Let me know if I were wrong
TestPath = pd.read_csv('ADVDML1TestCurrentPath.tsv', sep="\t+")
TestPath.head(5)

# Q4
# part a
import os
if not os.path.exists('SubData'):
    os.makedirs('SubData')

# part b
TestPath = pd.read_csv(".\\SubData\\ADVDML1TestCurrentPath.tsv", sep="\t+")
TestPath.head(5)

# Q5
# part a
import os

os.listdir("C:\\Users\\fengh\\Desktop\\ParentData")

# part b
# I assume you want us to create parent folder outside
# then read file from subfolder 
os.chdir("C:\\Users\\fengh\\Desktop\\ParentData\\CurrentData")
TestPath = pd.read_csv("..\\ADVDML1TestCurrentPath.tsv", sep="\t+")
TestPath.head(5)

# Section 2
# Q6
# part a
import urllib.request
from urllib.request import Request, urlopen
# here is another way may not use urllib
# and it works
'''
url = 'https://github.com/kkParker/ClassData/raw/master/Python/ADVDML2Mike.csv'
df = pd.read_csv(url, index_col=0, parse_dates=[0])
print(df)
'''
# something missing on the slides when use .read_csv
# if not add inedx and parse thing, it never works
response = urllib.request.urlopen("https://github.com/kkParker/ClassData/raw/master/Python/ADVDML2Sue.csv")
dfSue = pd.read_csv(response, index_col=0, parse_dates=[0])
dfSue.head(5)

response = urllib.request.urlopen("https://github.com/kkParker/ClassData/raw/master/Python/ADVDML2Mike.csv")
dfMike = pd.read_csv(response, index_col=0, parse_dates=[0])
dfMike.head(5)

# part b
dfSue.Flavor[dfSue.Flavor==1] = "Chocolate"
dfSue.Flavor[dfSue.Flavor==2] = "Vanilla"
dfSue.Flavor[dfSue.Flavor==3] = "Mixed"
dfSue.head(5)
dfMike.Flavor[dfMike.Flavor==1] = "Chocolate"
dfMike.Flavor[dfMike.Flavor==2] = "Vanilla"
dfMike.Flavor[dfMike.Flavor==3] = "Mixed"
dfMike.head(5)

# Q7
import matplotlib.pyplot as plt
import numpy as np

counts = pd.value_counts(dfSue.Flavor)
counts = pd.DataFrame(counts)
plt.grid(True)
objects = tuple(counts.index)
plt.bar(np.arange(len(counts.index)), counts.Flavor)
plt.xticks(np.arange(3),objects)
plt.title("Barchart of Sue's Flavor")
plt.xlabel('Flavors')
plt.ylabel('Counts')
plt.show()

# Q8
# part a
counts = pd.value_counts(dfMike.Flavor)
counts = pd.DataFrame(counts)
plt.grid(True)
objects = tuple(counts.index)
plt.bar(np.arange(len(counts.index)), counts.Flavor)
plt.xticks(np.arange(3),objects)
plt.title("Barchart of Mike's Flavor")
plt.xlabel('Flavors')
plt.ylabel('Counts')
plt.show()

# part b
def barchart(x, y, xlabel, ylabel, xticksnames, title):
    plt.bar(x,y,width=.5)
    plt.xlabel(xlabel)
    plt.ylabel(ylabel)
    plt.xticks(x,xticksnames)
    plt.title(title)
    plt.show()
    
y = counts.Flavor
x = np.arange(len(counts.index))
xlabel = 'Flavors'
ylabel = 'Counts'
xticksnames = objects
title = "Barchart of Mike's Flavor" 
barchart(x,y,xlabel,ylabel,xticksnames,title)

# part c
from bs4 import BeautifulSoup

url = "https://github.com/kkParker/ClassData/tree/master/Python"
response = urllib.request.urlopen(url)
html = response.read()
soup = BeautifulSoup(html, "lxml")
print(soup)