Data science tools
Want more content like this? Subscribe here to be notified of new releases!
Data science tools
Data visualization R-Python conversion guide
ggplot2 matplotlib seaborn
By Afshine Amidi and Shervine Amidi
General structure
Basic plots The main basic plots are summarized in the table below:
| Type | R command | Python command |
| Scatter plot | geom_point(
x, y, color, size, fill, alpha
) |
sns.scatterplot(
x, y, hue, size
) |
| Line plot | geom_line(
x, y, color, size, fill, alpha,
linetype
) |
sns.lineplot(
x, y, hue, size
) |
| Bar chart Histogram |
geom_bar(
x, y, color, size, fill, alpha
) |
sns.barplot(
x, y, hue
) |
| Box plot | geom_boxplot(
x, y, color
) |
sns.boxplot(
x, y, hue
) |
| Heatmap | geom_tile(
x, y, color, fill
) |
sns.heatmap(
data, cmap, linecolor,
linewidth, cbar
) |
Advanced features
Additional elements We can add objects on the plot with the following commands:
| Type | R command | Python command |
| Line | geom_vline(
xintercept, linetype
) |
ax.axvline(
x, ymin, ymax, color,
linewidth, linestyle
) |
geom_hline(
yintercept, linetype
) |
ax.axhline(
y, xmin, xmax, color,
linewidth, linestyle
) |
|
| Rectangle | geom_rect(
xmin, xmax, ymin, ymax
) |
ax.axvspan(
xmin, xmax, ymin, ymax,
color, fill, alpha
) |
| Text | geom_text(
x, y, label,
hjust, vjust
) |
ax.text(
x, y, s, color
) |
Last touch
Legend The title of legends can be customized to the plot with the following command:
plot + labs(params)
params are summarized below:
| Element | R command | Python command |
| Title / subtitle of the plot | title = 'text' |
ax.set_title('text', loc, pad) |
subtitle = 'text' |
plt.suptitle('text', x, y, size, ha) |
|
| Title of the $x$ / $y$ axis | x = 'text' |
ax.set_xlabel('text') |
y = 'text' |
ax.set_ylabel('text') |
|
| Title of the size / color | size = 'text' / color = 'text' |
ax.get_legend_handles_labels() |
| Caption of the plot | caption = 'text' |
ax.text('text', x, y, fontsize) |
This results in the following plot:
