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import streamlit as st
import pandas as pd
import time
st.header("Plotting Time Series Data")
st.markdown("Users can load their time-series data in **.csv** format and select a particular feature and plot-type.\
Go ahead and use the sidebar on the left to upload your data files to start visualizing it!")
# Load and config
with st.sidebar:
plot = st.radio("Select the kind of visualization:",('Feature collection', 'Users comparison', 'Data distribution'))
file = st.file_uploader("Load CSV file", accept_multiple_files = False)
if file:
df = pd.read_csv(file, index_col = False)
# df.index = df['Unnamed: 0'].tolist()
try:
del df['Unnamed: 0']
except KeyError:
pass
if 'df' not in st.session_state:
st.session_state['df'] = df
st.success("Your data has been successfully loaded! 🤗")
if 'df' in st.session_state:
st.caption("Your uploaded data:")
st.dataframe(st.session_state.df)
else:
st.caption("Upload your data using the sidebar and select a plot-type to start :sunglasses:")
df_base = st.session_state.df if 'df' in st.session_state else pd.DataFrame()
n = len(df_base)
col1, col2 = st.columns(2)
# Prepare data
if not df_base.empty and n:
with col1:
st.info(f"Your data has {n} samples.")
slider_range = list(range(n))
n_plot = st.slider("How many samples do you want to plot in the same graph", slider_range[0]+1, slider_range[-1]+1, 5)
plot_it = st.button("Plot now! 📊")
if plot_it:
st.snow()
feature = "relative_pupil_dilation"
df_plot = df_base.head(n_plot)
df_plot = [ini_list.strip('][').split(',') for ini_list in df_plot[feature]]
df_plot = pd.DataFrame(df_plot)
df_plot.columns = [str(column) for column in range(len(df_plot.columns))]
if 'df_plot' not in st.session_state:
st.session_state['df_plot'] = df_plot
# Draw plot
if 'df_plot' in st.session_state:
with st.spinner(f"Drawing plot to visualize {plot.lower()}"):
st.caption("Your visualization:")
df_plot_t = df_plot.copy(deep=True).transpose()
df_plot_t.columns = [str(column) for column in range(len(df_plot_t.columns))]
st.line_chart(df_plot_t, y=list(df_plot_t.columns), height=400, width=600)
st.dataframe(df_plot_t)
with st.expander("See explanation"):
st.caption("The chart above shows...")
elif df_base.empty and file:
st.warning("Consider running outlier detection to clean your data!", icon="⚠️")
st.caption(f"developer:: session_state keys: {list(st.session_state.keys())}")
st.caption(f"what is the meaning of the x-axis, add to explanation")
st.caption(f"add sample data demo in another tab") |