Hi,
I have 10 data(rows) in table with 3 input columns and 4 output columns as shown in the attached image.
Based on the each row of the table, I am able to display the corresponding bar chart on the web page one below the other.
I wanted to re-arrange the those 10 bar charts as shown in the 2nd image below
Here is an idea combining st.columns with itertools.cycle.
import streamlit as st
import numpy as np
import pandas as pd
from itertools import cycle
import matplotlib.pyplot as plt
N_ROWS = 10
N_COLS = 4
data = pd.DataFrame({f"Column {i}": np.random.random(N_ROWS) for i in range(N_COLS)})
x = np.arange(N_COLS)
st.dataframe(data, use_container_width=True)
"*****"
cols = st.columns(3)
cols_cycle = cycle(cols)
for col, (k, row) in zip(cols_cycle, data.iterrows()):
with col:
fig, ax = plt.subplots(figsize=[3, 2])
ax.bar(x, row, fc="None", ec="purple")
ax.set_title(f"Row {k}")
ax.set_ylim(0, 1)
ax.spines[["top", "right"]].set_visible(False)
st.pyplot(fig, use_container_width=True)
@keshav_dk You can use pandas melt and Altair faceted charts to achieve this fairly simply. Attached is an example created for you.
