CODEWITHSUNDEEP
pythonmatplotlibplothistogram
wandermonk
wandermonk

Reputation: 7356

Setting the time interval and adding limits to the histograms in matplotlib

I am new to python as well as matplotlib. I am trying to plot trip data for each city using a histogram from matplotlib. Here is the sample data i am trying to plot.

Data:

     duration  month  hour day_of_week   user_type
0   15.433333      3    23    Thursday  Subscriber
1    3.300000      3    22    Thursday  Subscriber
2    2.066667      3    22    Thursday  Subscriber
3   19.683333      3    22    Thursday  Subscriber
4   10.933333      3    22    Thursday  Subscriber
5   19.000000      3    21    Thursday  Subscriber
6    6.966667      3    21    Thursday  Subscriber
7   17.033333      3    20    Thursday  Subscriber
8    6.116667      3    20    Thursday  Subscriber
9    6.316667      3    20    Thursday  Subscriber
10  11.300000      3    20    Thursday  Subscriber
11   8.300000      3    20    Thursday  Subscriber
12   8.283333      3    19    Thursday  Subscriber
13  36.033333      3    19    Thursday  Subscriber
14   5.833333      3    19    Thursday  Subscriber
15   5.350000      3    19    Thursday  Subscriber

Code:

def get_durations_as_list(filename):
        with open(filename, 'r') as f_in:
            reader = csv.reader(f_in)
            next(reader, None)
            for row in reader:
                if row[4] in ['Subscriber','Registered'] and float(row[0]) < 75:
                    subscribers.append(float(row[0]))
                elif row[4] in ['Casual','Customer'] and float(row[0]) < 75:
                    customers.append(float(row[0]))
            return subscribers,customers

data_files = ['./data/Washington-2016-Summary.csv','./data/Chicago-2016-Summary.csv','./data/NYC-2016-Summary.csv',]
for file in data_files:
    city = file.split('-')[0].split('/')[-1]
    subscribers,customers = get_durations_as_list(file)

plt.hist(subscribers,range=[min(subscribers),max(subscribers)],bins=5)
plt.title('Distribution of Subscriber Trip Durations for city {}'.format(city))
plt.xlabel('Duration (m)')
plt.show()

plt.hist(customers,range=[min(subscribers),max(subscribers)],bins=5)
plt.title('Distribution of Customers Trip Durations for city {}'.format(city))
plt.xlabel('Duration (m)')
plt.show()

Now the question is how to set the time interval to 5mins wide and how to plot only the trips which are less than 75mins.

I have gone through the documentation but it looks complicated. After reading few stackoverflow question i found that bins are used to set the time interval. Is my assumption correct.

Upvotes: 0

Views: 2602

Answers (3)

user3262242
user3262242

Reputation: 184

To set the interval of 5 mins with max duration as 75 min, you would need 15 intervals. Hence your bin size will be 75/5. you can write it either bins=int(75/5) or as @om tripathi suggested as numpy.arange(0,75,5). Also you need not filter the duration greater than 75 min in the data filtering stage. You can always set the range as range = range(0, 75) in histogram to discard values greater than 75.

e.g. pyplot.hist(data, bins=numpy.arange(0,75,15) ,range=(0, 75))

Upvotes: 0

om tripathi
om tripathi

Reputation: 300

yes, your assumption is very much correct you can use bins parameter as a sequence. in your case, it will be like.

 b = [ 0,  5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70]

you can use numpy to genrate the above list.

 bins = numpy.arange(0,75,5)

Also, you can use Subscriber and Customer data set in one go below is the function

def plot_duration_type(filename):
    city = filename.split('-')[0].split('/')[-1]
    with open(filename, 'r') as f_in:
        reader = csv.DictReader(f_in)
        subscriber_duration = []
        customer_duration = []
        for row in reader:
            if float(row['duration']) < 75 and row['user_type'] == 'Subscriber':
                subscriber_duration.append(float(row['duration']))
            elif float(row['duration']) < 75 and row['user_type'] == 'Customer':
                customer_duration.append(float(row['duration']))
    b = [ 0,  5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70]
    plt.hist([subscriber_duration, customer_duration], bins=b, color=['orange', 'green'],
                 label=['Subscriber', 'Customer'])
    title = "{} Distribution of Trip Durations".format(city)
    plt.title(title)
    plt.xlabel('Duration (m)')
    plt.show()

data_file = ['./data/Washington-2016-Summary.csv', './data/Chicago-2016-Summary.csv', './data/NYC-2016-Summary.csv']
for datafile in data_file:
    print(plot_duration_type(datafile))

Upvotes: 0

Martin Schmelzer
Martin Schmelzer

Reputation: 23889

I cannot try it out but here are my thoughts:

The bins argument can also be a sequence of bin edges. Therefore you can take the minimum and maximum of durations and create a sequence with a step size of 5 (here using the numpy library):

import numpy as np
sequence = np.arange(min(dat['duration']), max(dat['duration']), 5)

(Maybe you want to floor/ceil the minimum and maximum values to integers.) Here the code relies on the fact that I read the data using the pandas library. It can easily be filtered using pandas as well:

import pandas as pd
dat = pd.read_csv('YOURFILE.csv')
dat_filtered = dat[dat['duration'] < 75]

Happy Holidays.

Upvotes: 1

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