added docstring and removed unnecessary imported modules

plots.py

@@ -1,20 +1,26 @@
-import streamlit as st
-import matplotlib.pyplot as plt
-import numpy as np
-from mpl_toolkits.mplot3d import Axes3D
-import umap
 import pandas as pd
 from word2vec import *
-from sklearn.preprocessing import StandardScaler
 import plotly.express as px
-from sklearn.manifold import TSNE
 import pickle
 
 
 def make_3d_plot_tSNE(vectors_list, target_word, time_slice_model):
     """
-        Turn list of 100D vectors into a 3D plot using t-SNE and Plotly.
-        List structure: [(word, model_name, vector, cosine_sim)]
+        Create a 3D plot using t-SNE and Plotly from a list of 100-dimensional vectors.
+
+        vectors_list: list of tuples containing (word, model_name, vector, cosine_sim)
+            - word: the word in the model
+            - model_name: the name of the model
+            - vector: the 100-dimensional vector representation of the word
+            - cosine_sim: the cosine similarity of the word to the target word
+
+        target_word: the word for which the nearest neighbours are calculated and plotted
+
+        time_slice_model: the time slice model name used to extract 3D vector representations
+
+        Return: a tuple containing:
+            - fig: the Plotly 3D scatter plot figure
+            - df: a pandas DataFrame containing the words, their 3D vectors, and cosine similarities
     """
     word = target_word