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feat: update api spec to handle multi-plot with multiple layers (#5)
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,29 @@ | ||
| import seaborn as sns | ||
| import matplotlib.pyplot as plt | ||
| import pandas as pd | ||
| import numpy as np | ||
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| # Load example dataset | ||
| tips = sns.load_dataset("tips") | ||
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| # Prepare data for the bar chart (average total bill by day) | ||
| avg_bill = tips.groupby('day')['total_bill'].mean().reset_index() | ||
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| # Prepare data for the line chart (average tip by day) | ||
| avg_tip = tips.groupby('day')['tip'].mean().reset_index() | ||
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| # Start plotting | ||
| plt.figure(figsize=(10, 6)) | ||
| sns.set(style="whitegrid") | ||
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| # Create bar chart | ||
| bar = sns.barplot(x='day', y='total_bill', data=avg_bill, color='lightblue', label='Average Total Bill') | ||
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| # Create line chart | ||
| line = sns.lineplot(x='day', y='tip', data=avg_tip, sort=False, marker='o', color='red', label='Average Tip') | ||
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| # Adding legend | ||
| plt.legend() | ||
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| # Show the plot | ||
| plt.show() |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| { | ||
| "id": "figure-id", | ||
| "library": "seaborn", | ||
| "coordinate": "cartesian", | ||
| "layout": { | ||
| "rows": 1, | ||
| "columns": 1 | ||
| }, | ||
| "title": "Average Bill and Tip by Day of Week", | ||
| "panels": [ | ||
| { | ||
| "id": "panel-01", | ||
| "title": "Bar and Line Chart", | ||
| "axes": { | ||
| "x": "Day of the Week", | ||
| "y": "Amount in USD" | ||
| }, | ||
| "layers": [ | ||
| { | ||
| "type": "bar", | ||
| "selector": [], | ||
| "data": [ | ||
| { | ||
| "x": "Thur", | ||
| "y": 17.68 | ||
| }, | ||
| { | ||
| "x": "Fri", | ||
| "y": 17.15 | ||
| }, | ||
| { | ||
| "x": "Sat", | ||
| "y": 20.44 | ||
| }, | ||
| { | ||
| "x": "Sun", | ||
| "y": 21.41 | ||
| } | ||
| ] | ||
| }, | ||
| { | ||
| "type": "line", | ||
| "selector": [], | ||
| "data": [ | ||
| { | ||
| "x": "Thur", | ||
| "y": 2.77 | ||
| }, | ||
| { | ||
| "x": "Fri", | ||
| "y": 2.73 | ||
| }, | ||
| { | ||
| "x": "Sat", | ||
| "y": 2.99 | ||
| }, | ||
| { | ||
| "x": "Sun", | ||
| "y": 3.26 | ||
| } | ||
| ] | ||
| } | ||
| ] | ||
| } | ||
| ] | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,65 @@ | ||
| # Load the required libraries | ||
| library(ggplot2) | ||
| library(palmerpenguins) | ||
| library(svglite) | ||
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| # Load the penguins dataset | ||
| data("penguins") | ||
| penguins <- na.omit(penguins) | ||
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| # Create a ggplot | ||
| p <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) + | ||
| geom_point() + | ||
| facet_grid(species ~ sex) + | ||
| labs( | ||
| title = "Penguin Bill Dimensions by Species and Sex", | ||
| x = "Bill Length (mm)", | ||
| y = "Bill Depth (mm)" | ||
| ) + | ||
| theme( | ||
| plot.title = element_text(size = 16, hjust = 0.5), | ||
| strip.text = element_text(size = 12), | ||
| axis.title = element_text(size = 12) | ||
| ) | ||
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| # Save the plot as an SVG file using ggsave and svglite | ||
| ggsave("multi-panel.svg", plot = p, device = svglite, width = 10, height = 8) | ||
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| # Extract raw data used for plotting per panel | ||
| plot_data <- ggplot_build(p)$data[[1]] | ||
| # Split the data by panel | ||
| plot_data_split <- split(plot_data, plot_data$PANEL) | ||
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| # Save each panel data as a separate data frame object | ||
| panel_data_list <- lapply(names(plot_data_split), function(panel) { | ||
| panel_data <- plot_data_split[[panel]] | ||
| assign(paste0("panel_data_", panel), panel_data, envir = .GlobalEnv) | ||
| return(panel_data) | ||
| }) | ||
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| # Assign names to the list elements for easier reference | ||
| names(panel_data_list) <- names(plot_data_split) | ||
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| # Load the required library for JSON | ||
| library(jsonlite) | ||
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| # Save each panel data as a JSON file containing only x and y variables | ||
| lapply(names(panel_data_list), function(panel) { | ||
| panel_data <- panel_data_list[[panel]][, c("x", "y")] | ||
| json_file <- paste0("panel_data_", panel, ".json") | ||
| write_json(panel_data, json_file) | ||
| }) | ||
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| # Extract the layout information to get the panel titles | ||
| layout_info <- ggplot_build(p)$layout$layout | ||
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| # Create a data frame that maps panel numbers to species and sex | ||
| panel_mapping <- data.frame( | ||
| PANEL = layout_info$PANEL, | ||
| species = layout_info$species, | ||
| sex = layout_info$sex | ||
| ) | ||
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| print(panel_mapping) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,36 @@ | ||
| import matplotlib.pyplot as plt | ||
| import seaborn as sns | ||
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| # Load the penguins dataset using seaborn | ||
| penguins = sns.load_dataset("penguins") | ||
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| # Get unique species and sexes | ||
| species = penguins["species"].dropna().unique() | ||
| sexes = penguins["sex"].dropna().unique() | ||
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| # Create a figure and a grid of subplots | ||
| fig, axes = plt.subplots( | ||
| nrows=len(species), ncols=len(sexes), figsize=(12, 8), sharex=True, sharey=True | ||
| ) | ||
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| # Set a global title for the figure | ||
| fig.suptitle("Penguin Bill Dimensions by Species and Sex", fontsize=16) | ||
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| # Loop through species and sexes to create each subplot | ||
| for i, sp in enumerate(species): | ||
| for j, sex in enumerate(sexes): | ||
| ax = axes[i, j] | ||
| subset = penguins[(penguins["species"] == sp) & (penguins["sex"] == sex)] | ||
| ax.scatter(subset["bill_length_mm"], subset["bill_depth_mm"]) | ||
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| # Set panel-specific titles | ||
| ax.set_title(f"{sp} - {sex}", fontsize=12) | ||
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| # Set x and y labels for the leftmost and bottom plots only | ||
| if i == len(species) - 1: | ||
| ax.set_xlabel("Bill Length (mm)") | ||
| if j == 0: | ||
| ax.set_ylabel("Bill Depth (mm)") | ||
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| # Show the plot | ||
| plt.show() |
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