Spaces:
Runtime error
Runtime error
File size: 3,698 Bytes
c6b92c7 072885d 12dcaf7 072885d 5554539 b827309 5554539 6e73e6e 5554539 6e73e6e 3f3bffe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 |
import streamlit as st
import pandas as pd
import bertopic
import plotly.express as px
import matplotlib as mp
st.set_page_config(page_title="Topic Modeling with Bertopic")
from datasets import load_dataset
st.markdown("""
https://github.com/pinecone-io/examples/tree/master/learn/algos-and-libraries/bertopic
""")
# data = load_dataset('jamescalam/python-reddit')
data = load_dataset("awacke1/LOINC-Panels-and-Forms")
from datasets import load_dataset
geo = load_dataset('jamescalam/world-cities-geo', split='train')
st.write(geo)
import plotly.express as px
palette = ['#1c17ff', '#faff00', '#8cf1ff', '#000000', '#030080', '#738fab']
fig = px.scatter_3d(
x=geo['x'], y=geo['y'], z=geo['z'],
color=geo['continent'],
custom_data=[geo['country'], geo['city']],
color_discrete_sequence=palette
)
fig.update_traces(
hovertemplate="\n".join([
"city: %{customdata[1]}",
"country: %{customdata[0]}"
])
)
fig.write_html("umap-earth-3d.html", include_plotlyjs="cdn", full_html=False)
import numpy as np
geo_arr = np.asarray([geo['x'], geo['y'], geo['z']]).T
geo_arr = geo_arr / geo_arr.max()
st.markdown(geo_arr[:5])
import umap
colors = geo['continent']
c_map = {
'Africa': '#8cf1ff',
'Asia': '#1c17ff',
'Europe': '#faff00',
'North America': '#738fab',
'Oceania': '#030080',
'South America': '#000000'
}
for i in range(len(colors)):
colors[i] = c_map[colors[i]]
colors[:5]
import matplotlib.pyplot as plt
import seaborn as sns
from tqdm.auto import tqdm
fig, ax = plt.subplots(3, 3, figsize=(14, 14))
nns = [2, 3, 4, 5, 10, 15, 30, 50, 100]
i, j = 0, 0
for n_neighbors in tqdm(nns):
fit = umap.UMAP(n_neighbors=n_neighbors)
u = fit.fit_transform(geo_arr)
sns.scatterplot(x=u[:,0], y=u[:,1], c=colors, ax=ax[j, i])
ax[j, i].set_title(f'n={n_neighbors}')
if i < 2: i += 1
else: i = 0; j += 1
target = geo['continent']
t_map = {
'Africa': 0,
'Asia': 1,
'Europe': 2,
'North America': 3,
'Oceania': 4,
'South America': 5
}
for i in range(len(target)):
target[i] = t_map[target[i]]
fig, ax = plt.subplots(3, 3, figsize=(14, 14))
nns = [2, 3, 4, 5, 10, 15, 30, 50, 100]
i, j = 0, 0
for n_neighbors in tqdm(nns):
fit = umap.UMAP(n_neighbors=n_neighbors)
u = fit.fit_transform(geo_arr, y=target)
sns.scatterplot(x=u[:,0], y=u[:,1], c=colors, ax=ax[j, i])
ax[j, i].set_title(f'n={n_neighbors}')
if i < 2: i += 1
else: i = 0; j += 1
import umap
fit = umap.UMAP(n_neighbors=50, min_dist=0.5)
u = fit.fit_transform(geo_arr)
fig = px.scatter(
x=u[:,0], y=u[:,1],
color=geo['continent'],
custom_data=[geo['country'], geo['city']],
color_discrete_sequence=palette
)
fig.update_traces(
hovertemplate="\n".join([
"city: %{customdata[1]}",
"country: %{customdata[0]}"
])
)
fig.write_html("umap-earth-2d.html", include_plotlyjs="cdn", full_html=False)
import pandas as pd
umapped = pd.DataFrame({
'x': u[:,0],
'y': u[:,1],
'continent': geo['continent'],
'country': geo['country'],
'city': geo['city']
})
umapped.to_csv('umapped.csv', sep='|', index=False)
from sklearn.decomposition import PCA
pca = PCA(n_components=2) # this means we will create 2-d space
p = pca.fit_transform(geo_arr)
fig = px.scatter(
x=p[:,0], y=p[:,1],
color=geo['continent'],
custom_data=[geo['country'], geo['city']],
color_discrete_sequence=palette
)
fig.update_traces(
hovertemplate="\n".join([
"city: %{customdata[1]}",
"country: %{customdata[0]}"
])
)
fig.write_html("pca-earth-2d.html", include_plotlyjs="cdn", full_html=False)
|