Today I learned a lot in Python

Get current directory

import os
os.getcwd()

Reading CSVs in Python

import csv
with open('/photo_dates_location.csv') as f:
    reader = csv.reader(f, delimiter=',', quotechar='"')
    reader.next() #skip header
    day_csv = [row[0] for row in reader]

Counting in Python

Using Counter to create a list of unique items and counts by appending items to the lists:

import counter
days = []
count = []
for (k,v) in Counter(day_csv).iteritems():
    days.append(k)
    count.append(v)

Ordering lists with a lambda expression

According to Eric Davis the lambda expression is a good way to make quick expressions on the fly for organizing things like the Counter lists:

day_number = {
'Monday': 1,
'Tuesday': 2,
'Wednesday': 3,
'Thursday': 4,
'Friday': 5,
'Saturday': 6,
'Sunday': 7
}
days_sorted = sorted(Counter(day_csv).iteritems(), key=lambda e: day_number[e[0]])

Plotting with Python

Given that the lists days and count are built above by the Counter(), you can pass them to matplotlib for charting:

from matplotlib import pyplot as plt

######## Bar Chart ########
xs = [i + 0.1 for i, _ in enumerate(days)]
plt.bar(xs, count)
plt.ylabel("Number of photos taken")
plt.title("Photo frequency by day")
plt.xticks([i + 0.5 for i, _ in enumerate(days)], days)
plt.savefig('img/weekdays_bar.png')
plt.clf()

######## Pie chart ########
colors = ['red', 'orange', 'green', 'purple', 'lightcoral', 'lightskyblue', 'yellowgreen']
explode = [0, 0, 0, 0, 0, 0.1, 0]
plt.pie(count, explode=explode, labels=days, colors=colors, autopct='%1.1f%%')
plt.axis('equal')
plt.suptitle("Percent of total photos taken on a given day of the week", fontsize=18)
plt.savefig('img/weekdays_pie.png')
  • If you don’t want to save the images, you could just show them instead with plt.show()
  • plt.clf() clears the figure so you can plot something else on it. Otherwise you’d need to close it before continuing. plt.close() can do that.

Depending on the source CSV, the above creates these two charts: Photos by day of week count Photos by day of week percentage

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