Renfe Guru II: Exploratory Data Analysis

We analyze how train tickets price changes as departure time approaches

Posted by David Adrián Cañones Castellano on Tue 21 May 2019

Renfe trips scrapping exploratory data analysis (I)

Te goal if this analysis in answering the following:

  • Is our project feasible? There must be strong variations in ticket price between its release to market (about 2 months before departure) and departure date. The goal of the project is to take advantage of those variations to send automatic reminders to users.

python imports

In [19]:
from IPython.display import Image
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import plotly.graph_objs as go
from plotly.offline import (download_plotlyjs, 
                            init_notebook_mode, 
                            plot, 
                            iplot)
from plotly import io as pio
import random
import seaborn as sns

config

In [2]:
# plot styling

mpl.rcParams['figure.figsize'] = (19.2, 10.8)
mpl.rcParams['figure.dpi'] = 100
mpl.rcParams['font.size'] = 12
In [3]:
init_notebook_mode()