6. Analyzing the Sequence of Data with RNNs

Activity 6.01: Using a Simple RNN for a Time Series Prediction

Solution

1. Import the required libraries, as follows:

   import pandas as pd
   import matplotlib.pyplot as plt
   import torch
   from torch import nn, optim

2. Load the dataset and then slice it so that it contains all the rows but only the columns from index 1 to 52:

   data = pd.read_csv("Sales_Transactions_Dataset_Weekly.csv")
   data = data.iloc[:,1:53]
   data.head()

   The output is as follows:

   Figure 6.26: Displaying dataset for columns from index 1 to 52

3. Plot the weekly sales transactions of five randomly chosen products from the entire dataset. Use a random seed of 0 when performing random sampling in order to achieve the same results as in the current activity:

   plot_data = data.sample(5, random_state=0)
   x = range(1,53)
   plt.figure(figsize=(10,5))
   for i,row in plot_data.iterrows():
       plt.plot(x,row)
   plt.legend(plot_data.index)
   plt.xlabel("Weeks...