---

title: “Worldwide Development”

author: “Gapminder Analytics”

format: dashboard

---

```{python}

import plotly.express as px

df = px.data.gapminder()

df = df[df[‘continent’] != ‘Oceania’]

```

# Indicators

## Row {height=60%}

```{python}

#| title: GDP and Life Expectancy

px.scatter(

df, x=“gdpPercap”, y=“lifeExp”,

animation_frame=“year”, animation_group=“country”,

size=“pop”, color=“continent”, hover_name=“country”,

facet_col=“continent”, log_x=True, size_max=45,

range_x=[100,100000], range_y=[25,90]

)

```

## Row {height=40%}

```{python}

#| title: Population

px.area(df, x=“year”, y=“pop”, color=“continent”, line_group=“country”)

```

```{python}

#| title: Life Expectancy

px.line(df, x=“year”, y=“lifeExp”, color=“continent”, line_group=“country”)

```

# Data

 Learn more about the Gapminder dataset at <https://www.gapminder.org/data/documentation/>

```{python}

from itables import show

show(df, showIndex = False)

```