Introduction to Pandas and Matplotlib | LBOET | HOXFRAMEWORK
Hello and welcome! In this tutorial we will do a little bit of
data science work using matplotlib and pandas.
Lets get started,
Code 1 :
<!--
import pandas as pd
from matplotlib import *
import matplotlib.pyplot as plt
from matplotlib import style
style.use('fivethirtyeight')
mydataframe = pd.DataFrame({'entries':[34,12,6,6,5,10,10,102,230,215,112]},
index = [4,5,6,7,8,9,10,11,12,13,14])
print(mydataframe)
plt.ylabel("Kills in a videogame")
plt.xlabel("Round")
plt.plot(mydataframe[{'entries'}])
#You can also save it as pdf, or remove the bbox_inches but then it looks too zoomed in
plt.show()
-->
Code 2:
<!--
import pandas as pd
df1 = pd.DataFrame({'Year':[2001,2002,2003,2004],
'Games_won':[2,3,2,2],
'Money_gained':[50,55,65,55]})
df3 = pd.DataFrame({'Year':[2001,2002,2003,2004],
'Games_lost':[7,8,9,6],
'Money_spent':[20,33,19,49]})
merged = pd.merge(df1,df3,on = 'Year',how= 'outer') #or inner ; this is if our data is different
merged.set_index('Year', inplace=True)
print("Videogame stats 2001-2004:\n")
print(merged)
-->
Code 3 (websitehits):
<!--
import csv
from matplotlib import *
import matplotlib.pyplot as plt
from matplotlib import style
import pandas as pd
style.use('fivethirtyeight')
day = []
views = []
with open('views.csv') as csv_file:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for row in csv_reader:
if line_count == 0:
print(f'Column names are {", ".join(row)}\n')
#what does this first one do
line_count += 1
else:
#why try?
try:
#
print(f'Day:{row[0]} , Month: {row[1]} , Views: {row[2]}')
#what are we doing here ?
day.append(row[0])
views.append(row[2])
#why dont we need {} ?
line_count += 1
except IndexError:
print("Done.")
mydataframe = pd.DataFrame({'views': views},index = day)
##mydataframe = mydataframe.sort_values(['views'], ascending=1)
##mydataframe = mydataframe.sort_index(ascending=1)
print(mydataframe)
plt.ylabel("Views")
plt.xlabel("Day")
plt.title("Website views per day - January 2019")
plt.plot(mydataframe['views'])
#plt.scatter(day,mydataframe['views'])
plt.savefig('website_hits.png', bbox_inches='tight')
plt.show()
-->
And views.csv:
<!--
day,month,views
1,January,50
2,January,60
3,January,70
4,January,70
5,January,75
6,January,80
7,January,90
8,January,120
9,January,150
10,January,250
11,January,200
12,January,320
13,January,435
14,January,120
15,January,150
-->
Thank you so much for visiting and have a nice day. :)
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