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import pandas as pd
import streamlit as st
import plotly.express as px
def streamlit_2columns_metrics_df_shape(df: pd.DataFrame):
(
column1name,
column2name,
) = st.columns(2)
with column1name:
st.metric(
label="Rows",
value=df.shape[0],
delta=None,
delta_color="normal",
)
with column2name:
st.metric(
label="Columns",
value=df.shape[1],
delta=None,
delta_color="normal",
)
def show_inputted_dataframe(data):
with st.expander("Input Dataframe:"):
st.dataframe(data)
streamlit_2columns_metrics_df_shape(data)
def standard_decomposition_plot(decomposition):
fig = decomposition.plot()
(xsize_standard_decomp, ysize_standard_decomp) = streamlit_chart_setting_height_width(
"Chart Size:", 5, 5, "xsize_standard_decomp", "ysize_standard_decomp")
fig.set_size_inches(xsize_standard_decomp, ysize_standard_decomp)
st.pyplot(fig)
def time_series_line_plot(data):
fig = px.line(
data
)
st.plotly_chart(fig, use_container_width=True)
def time_series_scatter_plot(data):
fig = px.scatter(data, trendline="ols")
st.plotly_chart(fig, use_container_width=True)
def time_series_box_plot(data):
fig = px.box(data, hover_data=['Date'], points="all")
st.plotly_chart(fig, use_container_width=True)
def time_series_violin_and_box_plot(graph_data):
fig = px.histogram(graph_data,
marginal="violin")
st.plotly_chart(fig, use_container_width=True)
def streamlit_chart_setting_height_width(
title: str,
default_widthvalue: int,
default_heightvalue: int,
widthkey: str,
heightkey: str,
):
with st.expander(title):
lbarx_col, lbary_col = st.columns(2)
with lbarx_col:
width_size = st.number_input(
label="Width in inches:",
value=default_widthvalue,
key=widthkey,
)
with lbary_col:
height_size = st.number_input(
label="Height in inches:",
value=default_heightvalue,
key=heightkey,
)
return width_size, height_size
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