geofacetpy 0.1.0

Easily create geofaceted plots in matplotlib

geofacetpy

geofacetpy is a Python library built to simplify the creation of geofaceted plots using matplotlib. It allows to easily map data to a grid layout and visualize trends across different regions using matplotlib and seaborn.

This library was heavily inspired by the R library geofacet.

Installation

pip install geofacetpy

Usage

Before you start [IMPORTANT]

Grid

Currently, the grid has to be a pandas DataFrame with specific columns - name, row, and col. There's a large repository of grids, which follow the same data structure at hafen/grid-desginer.

Custom plotting function

The custom plotting function, that is supplied to the geofacet() must take the following arguments

• ax (Axes object),
• data
• group_name (name of the grid element)
• and all other arguments, such as column names to be plotted

geofacet

group_column argument in the geofacet() is the name of the column in the data that is equivalent to the name in the grid layout and is the basis for the placement on the grid.

Examples

Previewing Grid Layout

from geofacet import preview_grid
import pandas as pd

grid = pd.read_csv("grid.csv")
preview_grid(grid)

Creating a geofacet plot

from geofacet import geofacet
import pandas as pd
import matplotlib.pyplot as plt

# Load data and grid layout
data = pd.read_csv("data_grouped.csv")
grid = pd.read_csv("grid.csv")

# Define a custom plotting function
def custom_plot(ax, data, group_name):
    ax.bar(data['col_x'], data['col_y'], color="blue")
    ax.set_title(group_name.replace(" ", "\n"), fontsize=8)
    ax.tick_params(axis="x", labelsize=8)
    ax.grid(True, linestyle="--", linewidth=0.5)

# Create the geofaceted plot
fig = geofacet(
    grid_layout=grid,
    data=data,
    group_column="district",
    plotting_function=custom_plot,
    figure_size=(11, 9),
    grid_spacing=(0.5, 0.5),
    sharex=True,
    sharey=True,
)

# Add titles and labels
fig.suptitle("Example Geofaceted Plot")
fig.supxlabel("Year")
fig.supylabel("Count")
plt.tight_layout()
plt.show()

Creating a Geofacet Plot with Seaborn

from geofacet import geofacet
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Load data and grid layout
data = pd.read_csv("data_grouped.csv")
grid = pd.read_csv("grid.csv")

# Define a custom plotting function using Seaborn
def seaborn_plot(ax, data, group_name):
    sns.lineplot(ax=ax, data=data, x='col_x', y='col_y', marker="o")
    ax.set_title(group_name.replace(" ", "\n"), fontsize=8)
    ax.tick_params(axis="x", labelsize=8)
    ax.grid(True, linestyle="--", linewidth=0.5)

# Create the geofaceted plot
fig = geofacet(
    grid_layout=grid,
    data=data,
    group_column="district",
    plotting_function=seaborn_plot,
    col_x="year",
    col_y="count",
    figure_size=(11, 9),
    grid_spacing=(0.5, 0.5),
    sharex=True,
    sharey=True,
)

# Add titles and labels
fig.suptitle("Geofaceted Plot with Seaborn")
fig.supxlabel("Year")
fig.supylabel("Count")
plt.tight_layout()
plt.show()

Output Example

Contributing

Feel free to open an issue for suggestions, report bugs, or submit a pull request to improve the library.

License

This project is licensed under the MIT License. See the LICENSE file for details.