May 19

Library Import in Python for ML/Graph ML

import libraries

import os
import pandas as pd
import math

Import Libraries for Graph, GNN (Graph Neural Network), and GCN (Graph Convolutional Network)

import stellargraph as sg
from stellargraph import StellarGraph
from stellargraph.layer import DeepGraphCNN
from stellargraph.mapper import FullBatchNodeGenerator
from stellargraph.mapper import PaddedGraphGenerator
from stellargraph.layer import GCN

Machine Learning related library Imports (Tensorflow)

from tensorflow.keras import layers, optimizers, losses, metrics, Model
from sklearn import preprocessing, model_selection
from IPython.display import display, HTML
import matplotlib.pyplot as plt
%matplotlib inline
from tensorflow.keras.layers import Dense, Conv1D, MaxPool1D, Dropout, Flatten
from tensorflow import keras

#how to read data from csv files
df_s = pd.read_csv("./data/" + data_file, low_memory = False);
df_s.head()

Convert Data Type and Sort Data

convert Date field to be a Date Type

df_s["Date"] = df_s["Date"].astype(‘datetime64[ns]’)

Sort data by date although this is no longer needed as data already is sorted when I generated data

df_s = df_s.sort_values( by = ['Ticker','Date'], ascending = True )

df_s = df_s.sort_values( by = ‘Date’, ascending = True )
df_s.head()

drop not available data

df_s_transpose = df_s_transpose.dropna(axis = 1);