country_indicators.py

from typing import Tuple

import pandas as pd
import plotly.express as px
import streamlit as st
import pathlib


DATA_LOCAL = pathlib.Path(__file__).parent / "country_indicators.csv"

DATA_URL = (
    "https://gist.githubusercontent.com/chriddyp/cb5392c35661370d95f300086accea51/"
    "raw/8e0768211f6b747c0db42a9ce9a0937dafcbd8b2/indicators.csv"
)


def create_plot(df: pd.DataFrame, x_indicator: str, y_indicator: str, year_range: Tuple[int, int]) -> "plotly.Fig":
    _df = df[df["Year"].between(*year_range)]
    xs = _df[_df["Indicator Name"] == x_indicator]
    ys = _df[_df["Indicator Name"] == y_indicator]

    dataframe = pd.merge(xs, ys, how="inner", on=["Country Name", "Year"])
    title = f"Country Indicators"
    fig = px.scatter(dataframe, x="Value_x", y="Value_y", title=title, height=400)
    fig.update_layout(dict(xaxis=dict(title=dict(text=x_indicator))))
    fig.update_layout(dict(yaxis=dict(title=dict(text=y_indicator))))
    return fig


def prepare_plot(df):
    available_indicators = df["Indicator Name"].unique()
    min_value = min(df["Year"])
    max_value = max(df["Year"])

    x_indicator = st.selectbox("Select indicator x", available_indicators, 0)
    y_indicator = st.selectbox("Select indicator y", available_indicators, 1)
    plotly_chart = st.empty()

    # Hack to seperate plot and slider
    st.markdown("<br><br>", unsafe_allow_html=True)
    year_range = st.slider(
        "Select min and max Year",
        min_value=min_value,
        max_value=max_value,
        value=[min_value, max_value],
    )

    fig = create_plot(df, x_indicator, y_indicator, year_range)
    plotly_chart.plotly_chart(fig, width=0, height=300)
    # st.plotly_chart(fig, width=0, height=300)


@st.cache(show_spinner=False)
def get_dataframe(url) -> pd.DataFrame:
    return pd.read_csv(url)


def get_data_from_url(url: str, local: pathlib.Path) -> pd.DataFrame:
    if local.exists():
        df = get_dataframe(local.as_posix())
    else:
        df = get_dataframe(url)
        df.to_csv(local, index=False)
    return df


st.markdown("""## Country Indicators - Streamlit version""")

data = get_data_from_url(DATA_URL, DATA_LOCAL)
prepare_plot(data)