code: def gapminder(
      datetimes=False, centroids=False, year=None, pretty_names=False
  ):
      """
      Each row represents a country on a given year.
  
      https://www.gapminder.org/data/
  
      Returns:
          A `pandas.DataFrame` with 1704 rows and the following columns:
          `['country', 'continent', 'year', 'lifeExp', 'pop', 'gdpPercap',
          'iso_alpha', 'iso_num']`.
          If `datetimes` is True, the 'year' column will be a datetime column
          If `centroids` is True, two new columns are added: ['centroid_lat', 'centroid_lon']
          If `year` is an integer, the dataset will be filtered for that year
      """
      df = _get_dataset("gapminder")
      if year:
          df = df[df["year"] == year]
      if datetimes:
          df["year"] = (df["year"].astype(str) + "-01-01").astype(
              "datetime64[ns]"
          )
      if not centroids:
          df = df.drop(["centroid_lat", "centroid_lon"], axis=1)
      if pretty_names:
          df.rename(
              mapper=dict(
                  country="Country",
                  continent="Continent",
                  year="Year",
                  lifeExp="Life Expectancy",
                  gdpPercap="GDP per Capita",
                  pop="Population",
                  iso_alpha="ISO Alpha Country Code",
                  iso_num="ISO Numeric Country Code",
                  centroid_lat="Centroid Latitude",
                  centroid_lon="Centroid Longitude",
              ),
              axis="columns",
              inplace=True,
          )
      return df
  
file_path: plotly.py/packages/python/plotly/plotly/data/__init__.py
label_desc: Use image node_id 1 for calling a global function with example usage: gapminder(datetimes, centroids, year, pretty_names) and returns: df