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import streamlit as st
from util import developer_info_static
from src.plot import list_all, distribution_histogram, distribution_boxplot, count_Y, box_plot, violin_plot, strip_plot, density_plot ,multi_plot_heatmap, multi_plot_scatter, multi_plot_line, word_cloud_plot, world_map, scatter_3d
def display_word_cloud(text):
_, word_cloud_col, _ = st.columns([1, 3, 1])
with word_cloud_col:
word_fig = word_cloud_plot(text)
if word_fig == -1:
st.error('Data not supported')
else:
st.pyplot(word_cloud_plot(text))
def data_visualization(DF):
st.divider()
st.subheader('Data Visualization')
attributes = DF.columns.tolist()
# Three tabs for three kinds of visualization
single_tab, multiple_tab, advanced_tab = st.tabs(['Single Attribute Visualization', 'Multiple Attributes Visualization', 'Advanced Visualization'])
# Single attribute visualization
with single_tab:
_, col_mid, _ = st.columns([1, 5, 1])
with col_mid:
plot_area = st.empty()
col1, col2 = st.columns(2)
with col1:
att = st.selectbox(
label = 'Select an attribute to visualize:',
options = attributes,
index = len(attributes)-1
)
st.write(f'Attribute selected: :green[{att}]')
with col2:
plot_types = ['Donut chart', 'Violin plot', 'Distribution histogram', 'Boxplot', 'Density plot', 'Strip plot', 'Distribution boxplot']
plot_type = st.selectbox(
key = 'plot_type1',
label = 'Select a plot type:',
options = plot_types,
index = 0
)
st.write(f'Plot type selected: :green[{plot_type}]')
if plot_type == 'Distribution histogram':
fig = distribution_histogram(DF, att)
plot_area.pyplot(fig)
elif plot_type == 'Distribution boxplot':
fig = distribution_boxplot(DF, att)
if fig == -1:
plot_area.error('The attribute is not numeric')
else:
plot_area.pyplot(fig)
elif plot_type == 'Donut chart':
fig = count_Y(DF, att)
plot_area.plotly_chart(fig)
elif plot_type == 'Boxplot':
fig = box_plot(DF, [att])
plot_area.plotly_chart(fig)
elif plot_type == 'Violin plot':
fig = violin_plot(DF, [att])
plot_area.plotly_chart(fig)
elif plot_type == 'Strip plot':
fig = strip_plot(DF, [att])
plot_area.plotly_chart(fig)
elif plot_type == 'Density plot':
fig = density_plot(DF, att)
plot_area.plotly_chart(fig)
# Multiple attribute visualization
with multiple_tab:
col1, col2 = st.columns([6, 4])
with col1:
options = st.multiselect(
label = 'Select multiple attributes to visualize:',
options = attributes,
default = []
)
with col2:
plot_types = ["Violin plot", "Boxplot", "Heatmap", "Strip plot", "Line plot", "Scatter plot"]
plot_type = st.selectbox(
key = 'plot_type2',
label = 'Select a plot type:',
options = plot_types,
index = 0
)
_, col_mid, _ = st.columns([1, 5, 1])
with col_mid:
plot_area = st.empty()
if options:
if plot_type == 'Scatter plot':
fig = multi_plot_scatter(DF, options)
if fig == -1:
plot_area.error('Scatter plot requires two attributes')
else:
plot_area.pyplot(fig)
elif plot_type == 'Heatmap':
fig = multi_plot_heatmap(DF, options)
if fig == -1:
plot_area.error('The attributes are not numeric')
else:
plot_area.pyplot(fig)
elif plot_type == 'Boxplot':
fig = box_plot(DF, options)
if fig == -1:
plot_area.error('The attributes are not numeric')
else:
plot_area.plotly_chart(fig)
elif plot_type == 'Violin plot':
fig = violin_plot(DF, options)
if fig == -1:
plot_area.error('The attributes are not numeric')
else:
plot_area.plotly_chart(fig)
elif plot_type == 'Strip plot':
fig = strip_plot(DF, options)
if fig == -1:
plot_area.error('The attributes are not numeric')
else:
plot_area.plotly_chart(fig)
elif plot_type == 'Line plot':
fig = multi_plot_line(DF, options)
if fig == -1:
plot_area.error('The attributes are not numeric')
elif fig == -2:
plot_area.error('Line plot requires two attributes')
else:
plot_area.pyplot(fig)
# Advanced visualization
with advanced_tab:
st.subheader("3D Scatter Plot")
column_1, column_2, column_3 = st.columns(3)
with column_1:
x = st.selectbox(
key = 'x',
label = 'Select the x attribute:',
options = attributes,
index = 0
)
with column_2:
y = st.selectbox(
key = 'y',
label = 'Select the y attribute:',
options = attributes,
index = 1 if len(attributes) > 1 else 0
)
with column_3:
z = st.selectbox(
key = 'z',
label = 'Select the z attribute:',
options = attributes,
index = 2 if len(attributes) > 2 else 0
)
if st.button('Generate 3D Plot'):
_, fig_3d_col, _ = st.columns([1, 3, 1])
with fig_3d_col:
fig_3d_1 = scatter_3d(DF, x, y, z)
if fig_3d_1 == -1:
st.error('Data not supported')
else:
st.plotly_chart(fig_3d_1)
st.divider()
st.subheader('World Cloud')
upload_txt_checkbox = st.checkbox('Upload a new text file instead')
if upload_txt_checkbox:
uploaded_txt = st.file_uploader("Choose a text file", accept_multiple_files=False, type="txt")
if uploaded_txt:
text = uploaded_txt.read().decode("utf-8")
display_word_cloud(text)
else:
text_attr = st.selectbox(
label = 'Select the text attribute:',
options = attributes,
index = 0)
if st.button('Generate Word Cloud'):
text = DF[text_attr].astype(str).str.cat(sep=' ')
display_word_cloud(text)
st.divider()
st.subheader('World Heat Map')
col_1, col_2 = st.columns(2)
with col_1:
country_col = st.selectbox(
key = 'country_col',
label = 'Select the country attribute:',
options = attributes,
index = 0
)
with col_2:
heat_attribute = st.selectbox(
key = 'heat_attribute',
label = 'Select the attribute to display in heat map:',
options = attributes,
index = len(attributes) - 1
)
if st.button("Show Heatmap"):
_, map_col, _ = st.columns([1, 3, 1])
with map_col:
world_fig = world_map(DF, country_col, heat_attribute)
if world_fig == -1:
st.error('Data not supported')
else:
st.plotly_chart(world_fig)
st.divider()
# Data Overview
st.subheader('Data Overview')
if 'data_origin' not in st.session_state:
st.session_state.data_origin = DF
st.dataframe(st.session_state.data_origin.describe(), width=1200)
if 'overall_plot' not in st.session_state:
st.session_state.overall_plot = list_all(st.session_state.data_origin)
st.pyplot(st.session_state.overall_plot)
st.divider()
developer_info_static() |