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documentation/02.2-eda-plotly.md
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@@ -542,52 +542,280 @@ aux éléments du dessin.
```python {.numberLines}
import pandas as pd
from plotly import express as px
from plotly.colors import qualitative
data = pd.DataFrame(data={
"product": ["pomme", "poire", "banane", "pêche"],
"price": [1.99, 2.49, 2.99, 3.49], "wpu": [200, 180, 140, 200]
"name": ["headphones", "microphone", "speaker", "powerbank", "tablet", "laptop"],
"price": [99.99, 49.99, 149.99, 29.99, 199.99, 499.99],
"merchant": ["amazon", "amazon", "bestbuy", "amazon", "newegg", "amazon"],
"color": ["black", "silver", "white", "red", "gray", "silver"]
})
figure = px.pie(data, values="price", names="product", title="Prix", color_discrete_sequence=["red", "orange", "yellow", "#8F0"])
figure.layout.update({"template": "seaborn", "title": "Prix au kilo", "font": {"family": "Cabin", "size": 13}})
figure.show()
figure = px.pie(data, values="price", names="name", title="Prix", texttemplate="", color_discrete_sequence=qualitative.Bold)
figure.layout.update({"template": "seaborn", "title": "Prix à l'unité", "font": {"family": "Cabin", "size": 13}})
figure.show(renderer="browser")
```
Plotly Express fournit des séquences ou dégradés de couleurs, dont la référence est disponible ci-dessous :
----
[Couleurs et séquences de couleurs](https://plotly.com/python/discrete-color/)
![Rendu avec choix de couleurs par secteur](assets/images/eda-plotly-express-pie-colors-predefined.png)
----
![Rendu avec choix de couleurs par secteur](assets/images/eda-plotly-express-pie-colors.png)
### Gradients de couleurs
----
### Couleur dépendante de la valeur
Vous pouvez sur certains graphiques définir un gradient à appliquer aux éléments du dessin
selon une valeur qui leur est associée. Ici, nous avons un graphique en barres, où la couleur
de chaque barre dépend de la valeur de la colonne `price`.
Vous pouvez appliquer des couleurs prédéfinies ou continues à vos graphiques. Vous pouvez utiliser une palette
servant de dégradé pour colorier les éléments du dessin selon une valeur associée.
```python {.numberLines}
import pandas as pd
from plotly import express as px
from plotly.colors import sequential, qualitative
data = pd.DataFrame(data={
"product": ["pomme", "poire", "banane", "pêche"],
"price": [1.99, 2.49, 2.99, 3.49], "wpu": [200, 180, 140, 200]
df = pd.DataFrame(data={
"month": [f"2005-{i:02d}" for i in range(1, 13)],
"temperature": [4.4, 6.8, 9.2, 11.5, 13.8, 16.3, 19.1, 21.4, 22.9, 20.5, 17.2, 13.9]
})
figure = px.bar(data, y="price", x="product", title="Prix", color="price", color_continuous_scale=["red", "orange", "yellow", "#8F0"])
figure.layout.update({"template": "seaborn", "title": "Prix au kilo", "font": {"family": "Cabin", "size": 13}})
figure.show()
plot = px.bar(
df, x="month", y="temperature", color="temperature", template="seaborn",
title="Temperatures mensuelles de 2005",
color_continuous_scale=sequential.Turbo,
labels={"month": "Mois", "temperature": "Température (°C)"}
)
plot.layout.update({"font": {"family": "Cabin", "size": 13}})
plot.show()
```
Ici, l'argument `color` permet d'indiquer sur les valeurs de quelle colonne colorier les barres.
L'argument `color_continuous_scale` permet de définir les couleurs d'un dégradé à utiliser pour
colorier les barres.
----
![Rendu avec gradient de couleurs](assets/images/eda-plotly-express-bar-gradient.png)
![Rendu avec choix de couleurs par valeur](assets/images/eda-plotly-express-bar-colors-predefined.png)
----
### Palettes de couleurs personnalisées
Les palettes utilisées dans les exemples précédents sont simplement des listes de couleurs prédéfinies
par Plotly, mais vous pouvez définir vos propres palettes de couleurs via des listes composées de couleurs sous plusieurs formats :
| Format de couleur | Exemple(s) | Description / notes |
| ------------------------ | -------------------------------- | ------------------------------------------------ |
| Nom de couleur CSS | `"red"`, `"blue"`, `"green"` | Noms de couleurs standards en CSS |
| Code hexadécimal | `"#FF5733"`, `"#33FF57"` | Codes hexadécimaux RGB |
| Code RGB | `"rgb(255,0,0)"`, `"rgb(0,255,0)"` | Codes RGB avec valeurs décimales (0-255) |
| Code RGBA | `"rgba(255,0,0,0.5)"` | Codes RGBA avec valeurs décimales (0-255) et alpha (0-1) |
----
Ici on définit manuellement une suite de couleurs à utiliser pour colorier les barres, allant du rouge au jaune.
```python {.numberLines}
import pandas as pd
from plotly import express as px
from plotly.colors import sequential, qualitative
df = pd.DataFrame(data={
"month": [f"2005-{i:02d}" for i in range(1, 13)],
"temperature": [4.4, 6.8, 9.2, 11.5, 13.8, 16.3, 19.1, 21.4, 22.9, 20.5, 17.2, 13.9]
})
plot = px.bar(
df, x="month", y="temperature", color="temperature", template="seaborn",
title="Temperatures mensuelles de 2005",
color_continuous_scale=["#FF0020", "rgb(255,165,0)", "rgba(255,255,0,0.8)"],
labels={"month": "Mois", "temperature": "Température (°C)"}
)
plot.layout.update({"font": {"family": "Cabin", "size": 13}})
plot.show()
```
----
![Rendu avec choix de couleurs par valeur](assets/images/eda-plotly-express-bar-colors-custom.png)
----
[Couleurs et séquences de couleurs](https://plotly.com/python/discrete-color/)
![Couleurs Qualitatives](assets/images/eda-plotly-colors-qualitative.svg)
----
[Couleurs et séquences de couleurs](https://plotly.com/python/discrete-color/)
![Séquences de Couleurs](assets/images/eda-plotly-colors-sequential.svg)
----
[Couleurs continues](https://plotly.com/python/builtin-colorscales/#builtin-sequential-color-scales)
![Couleurs continues](assets/images/eda-plotly-colors-continuous.svg)
----
### Sous-graphiques ([subplots]{.naming})
Plotly propose un module `plotly.subplots` permettant de créer des figures composées de plusieurs sous-graphiques.
Vous pouvez définir la mise en page de vos sous-graphiques, en précisant le nombre de lignes et de colonnes, ainsi que
la taille de chaque sous-graphe.
```python {.numberLines}
import pandas as pd
from plotly.subplots import make_subplots
from plotly.graph_objs import Figure, Bar
data = pd.DataFrame(data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600]
})
figure: Figure = make_subplots(rows=1, cols=2, subplot_titles=("Prix", "Poids unitaires"))
figure.add_trace(Bar(name="Prix", x=data["product"], y=data["price"]), row=1, col=1)
figure.add_trace(Bar(name="Poids", x=data["product"], y=data["weight"]), row=1, col=2)
figure.update_layout(template="seaborn", title="Prix et poids unitaires", font={"family": "Cabin", "size": 13})
figure.show(renderer="browser")
```
Vous pouvez également créer un objet `Figure`{.python} normalement, et exécuter la méthode `figure.set_subplots`{.python}
pour obtenir le même objet.
----
![Sous-graphiques](assets/images/eda-plotly-subplot-base.png)
----
#### Propriétés des colonnes et lignes
Vous pouvez définir les dimensions relatives des colonnes et lignes lors de la création de sous-graphiques.
```python {.numberLines}
import pandas as pd
from plotly.subplots import make_subplots
from plotly.graph_objs import Figure, Bar
data = pd.DataFrame(data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600]
})
figure: Figure = make_subplots(rows=1, cols=2, column_widths=[0.6, 0.4], row_heights=[1.0])
figure.add_trace(Bar(name="Prix", x=data["product"], y=data["price"]), row=1, col=1)
figure.add_trace(Bar(name="Poids", x=data["product"], y=data["weight"]), row=1, col=2)
figure.update_layout(template="seaborn", title="Prix et poids unitaires", font={"family": "Cabin", "size": 13})
figure.show(renderer="browser")
```
Ici les colonnes 1 et 2 représentent respectivement 60% et 40% de la largeur totale.
----
![Sous-graphiques avec largeurs de colonnes](assets/images/eda-plotly-subplot-widths-heights.png)
----
### Éléments graphiques
Vous pouvez agrémenter manuellement vos graphiques d'éléments visuels; les objets `Figure`{.python}
possèdent de nombreuses méthodes pour ajouter des éléments visuels (_images_, _rectangles_, autres…)
----
#### Ajouter une image
```python {.numberLines}
import pandas as pd
from plotly.graph_objs import Figure, Bar
from PIL import Image
data = pd.DataFrame(data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600]
})
figure: Figure = Figure(data=[Bar(name="Prix", x=data["product"], y=data["price"])])
figure.add_layout_image(
layer="above",
x=0,
y=1.02,
xref="paper",
yref="paper",
sizex=1,
sizey=0.075,
xanchor="left",
yanchor="bottom",
source=Image.open("images/python-logo-square.png")
)
figure.update_layout(template="seaborn", title="Prix et poids unitaires", font={"family": "Cabin", "size": 13})
figure.show(renderer="browser")
```
**Note** : Nécessite une image valide.
----
![Ajout d'une image de Logo](assets/images/eda-plotly-trace-image.png)
----
#### Options de taille, d'échelle et d'alignement
| Argument | Type / valeur possible | Description / notes |
|-----------|----------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `xref` | `"paper"` / `"pixel"` / `"x"` | Référence horizontale de l'image. Lorsque `xref` vaut `"paper"`, `x` est relative à la largeur totale du graphique. Lorsque `xref` vaut `"pixel"`, `x` est en pixels. |
| `yref` | `"paper"` / `"pixel"` / `"y"` | Référence verticale de l'image. Lorsque `yref` vaut `"paper"`, `y` est relative à la hauteur totale du graphique. Lorsque `yref` vaut `"pixel"`, `y` est en pixels. |
| `xanchor` | `"auto"` / `"left"` / `"center"` / `"right"` | Alignement horizontal de l'image selon `x`. |
| `yanchor` | `"auto"` / `"top"` / `"middle"` / `"bottom"` | Alignement vertical de l'image selon `y`. |
| `x` | nombre | Position horizontale de l'image (relative à `xref`). |
| `y` | nombre | Position verticale de l'image (relative à `yref`). |
| `sizex` | nombre ∈ [0, 1] | Largeur relative de l'image selon l'axe des X. |
| `sizey` | nombre ∈ [0, 1] | Hauteur relative de l'image selon l'axe des Y. |
| `layer` | `"above"` / `"below"` / `"between"` | Couche de l'image par rapport aux autres éléments du graphique. |
| `source` | `PIL.Image` | Image à afficher. |
----
#### Ajouter un rectangle horizontal
```python {.numberLines}
import pandas as pd
from plotly.graph_objs import Figure, Bar, Scatter
data = pd.DataFrame(
data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600],
}
)
figure: Figure = Figure(data=[Bar(name="Prix", x=data["product"], y=data["price"])])
figure.add_hrect(y0=2.75, y1=4.5, fillcolor="gray", opacity=0.25, layer="below")
figure.update_layout(
template="seaborn",
title="Prix et poids unitaires",
font={"family": "Cabin", "size": 13},
xaxis={"title": "Produit", "showgrid": False},
yaxis={"title": "Prix (€)", "showgrid": False}
)
figure.show(renderer="browser")
```
----
![Ajout d'un rectangle horizontal](assets/images/eda-plotly-trace-hrect.png)
----
#### Options de rectangle
| Argument | Type / valeur possible | Description / notes |
|-------------|-------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `y0` | nombre | Position verticale de la ligne en bas (relative à `yref`). |
| `y1` | nombre | Position verticale de la ligne en haut (relative à `yref`). |
| `yref` | `"paper"` / `"pixel"` / `"y"` | Référence verticale de la ligne. Lorsque `yref` vaut `"paper"`, `y` est relative à la hauteur totale du graphique. Lorsque `yref` vaut `"pixel"`, `y` est en pixels. |
| `fillcolor` | `str` (couleur HTML) | Couleur de remplissage de la ligne. |
| `line` | `dict` | Dictionnaire des propriétés de la ligne (voir la documentation de Plotly). |
| `opacity` | `float` ∈ [0, 1] | Opacité de la ligne. |
| `layer` | `"above"` / `"below"` / `"between"` | Couche de la ligne par rapport aux autres éléments du graphique. |
----

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import pandas as pd
from plotly import express as px
from plotly.colors import sequential, qualitative
df = pd.DataFrame(data={
"month": [f"2005-{i:02d}" for i in range(1, 13)],
"temperature": [4.4, 6.8, 9.2, 11.5, 13.8, 16.3, 19.1, 21.4, 22.9, 20.5, 17.2, 13.9]
})
plot = px.bar(
df, x="month", y="temperature", color="temperature", template="seaborn",
title="Temperatures mensuelles de 2005",
color_continuous_scale=sequential.Turbo,
labels={"month": "Mois", "temperature": "Température (°C)"}
)
plot.layout.update({"font": {"family": "Cabin", "size": 13}})
plot.show()

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import pandas as pd
from plotly import express as px
from plotly.colors import sequential, qualitative
df = pd.DataFrame(data={
"month": [f"2005-{i:02d}" for i in range(1, 13)],
"temperature": [4.4, 6.8, 9.2, 11.5, 13.8, 16.3, 19.1, 21.4, 22.9, 20.5, 17.2, 13.9]
})
plot = px.bar(
df, x="month", y="temperature", color="temperature", template="seaborn",
title="Temperatures mensuelles de 2005",
color_continuous_scale=["#FF0020", "rgb(255,165,0)", "rgba(255,255,0,0.8)"],
labels={"month": "Mois", "temperature": "Température (°C)"}
)
plot.layout.update({"font": {"family": "Cabin", "size": 13}})
plot.show()

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import pandas as pd
from plotly import express as px
from plotly.colors import qualitative
data = pd.DataFrame(data={
"name": ["headphones", "microphone", "speaker", "powerbank", "tablet", "laptop"],
"price": [99.99, 49.99, 149.99, 29.99, 199.99, 279.99],
"merchant": ["amazon", "amazon", "bestbuy", "amazon", "newegg", "amazon"],
"color": ["black", "silver", "white", "red", "gray", "silver"]
})
figure = px.pie(data, values="price", names="name", title="Prix", color_discrete_sequence=qualitative.Bold)
figure.layout.update({"template": "seaborn", "title": "Prix à l'unité", "font": {"family": "Cabin", "size": 13}, "width": 1080, "height": 720})
figure.update_traces(textposition="inside", textinfo="percent+label", texttemplate="%{label}<br>%{value}€ (%{percent:.2%})")
figure.show()

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import pandas as pd
from plotly._subplots import SubplotXY
from plotly.subplots import make_subplots
from plotly.graph_objs import Figure, Bar
data = pd.DataFrame(data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600]
})
figure: Figure = make_subplots(rows=1, cols=3, subplot_titles=("Prix", "Poids unitaires"))
subplot = figure.get_subplot(row=1, col=2)
subplot.xaxis["domain"] = [0.3555555, 1.0]
print(subplot, dir(subplot))
figure.add_trace(Bar(name="Prix", x=data["product"], y=data["price"]), row=1, col=1)
figure.add_trace(Bar(name="Poids", x=data["product"], y=data["weight"]), row=1, col=2)
figure.update_layout(template="seaborn", title="Prix et poids unitaires", font={"family": "Cabin", "size": 13})
figure.update_traces(row=1, col=2, specs=2)
figure.show(renderer="browser")

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import pandas as pd
from plotly.subplots import make_subplots
from plotly.graph_objs import Figure, Bar
data = pd.DataFrame(data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600]
})
figure: Figure = make_subplots(rows=1, cols=2, column_widths=[0.6, 0.4], row_heights=[1.0])
figure.add_trace(Bar(name="Prix", x=data["product"], y=data["price"]), row=1, col=1)
figure.add_trace(Bar(name="Poids", x=data["product"], y=data["weight"]), row=1, col=2)
figure.update_layout(template="seaborn", title="Prix et poids unitaires", font={"family": "Cabin", "size": 13})
figure.show()

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import plotly.express as px
from plotly.graph_objects import Figure, Scatter
COLS: int = 3
fig: Figure = px.colors.sequential.swatches_continuous()
fig3: Figure = px.colors.qualitative.swatches()
figb: Figure = px.colors.sequential.swatches()
fig2 = Figure(layout={
"title": "Palette de couleurs continues Plotly Sequential",
"font": {"family": "Cabin", "size": 13},
"xaxis": {"visible": False, "showticklabels": False},
"yaxis": {"visible": False, "showticklabels": False},
"legend": {"visible": False},
"width": 1400,
}).set_subplots(rows=22, cols=COLS)
for i, p in enumerate(fig.select_traces()): #type: int, Scatter
fig2.add_trace(p, row= (i // COLS) + 1, col=(i % COLS) + 1)
fig2.update_xaxes({"visible": False, "showticklabels": False, "showgrid": False})
fig2.update_yaxes({"visible": True, "showticklabels": True, "showgrid": False})
fig2.update_yaxes(tickfont={"size": 11}, ticksuffix=" ")
fig2.write_image("eda-plotly-colors-continuous.svg")
# fig2.show(renderer="browser")
fig4 = Figure(layout={
"title": "Palette de couleurs séquentielles Plotly Sequential",
"font": {"family": "Cabin", "size": 13},
"xaxis": {"visible": False, "showticklabels": False},
"yaxis": {"visible": False, "showticklabels": False},
"legend": {"visible": False},
"width": 1400,
"margin": {"t": 100, "b": 50, "l": 60, "r": 50},
}).set_subplots(rows=22, cols=COLS)
for i, p in enumerate(figb.select_traces()): #type: int, Scatter
fig4.add_trace(p, row= (i // COLS) + 1, col=(i % COLS) + 1)
fig4.update_xaxes({"visible": False, "showticklabels": False, "showgrid": False})
fig4.update_yaxes({"visible": True, "showticklabels": True, "showgrid": False})
fig4.update_yaxes(tickfont={"size": 11}, ticksuffix=" ")
fig4.write_image("eda-plotly-colors-sequential.svg")
fig3.update_layout({
"title": "Palette de couleurs qualitatives Plotly Qualitative",
"font": {"family": "Cabin", "size": 13},
"xaxis": {"visible": False, "showticklabels": False},
"yaxis": {"visible": False, "showticklabels": False},
"legend": {"visible": False},
"width": 1200,
"margin": {"t": 100, "b": 50, "l": 60, "r": 50},
})
fig3.update_xaxes({"visible": False, "showticklabels": False, "showgrid": False})
fig3.update_yaxes({"visible": True, "showticklabels": True, "showgrid": False})
fig3.update_yaxes(tickfont={"size": 11}, ticksuffix=" ")
fig3.write_image("eda-plotly-colors-qualitative.svg")

30
source/plotting/charts/plotly_trace_image.py Normal file
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@@ -0,0 +1,30 @@
import pandas as pd
from plotly.graph_objs import Figure, Bar
from PIL import Image
data = pd.DataFrame(
data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600],
}
)
figure: Figure = Figure(data=[Bar(name="Prix", x=data["product"], y=data["price"])])
figure.add_layout_image(
layer="above",
x=0,
y=1.02,
xref="paper",
yref="paper",
sizex=1,
sizey=0.075,
xanchor="left",
yanchor="bottom",
source=Image.open("images/python-logo-square.png"),
)
figure.update_layout(
template="seaborn",
title="Prix et poids unitaires",
font={"family": "Cabin", "size": 13},
)
figure.show(renderer="browser")

20
source/plotting/charts/plotly_trace_rectangle.py Normal file
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import pandas as pd
from plotly.graph_objs import Figure, Bar, Scatter
data = pd.DataFrame(
data={
"product": ["tarte", "gâteau", "biscuit", "mille-feuille", "éclair", "brownie"],
"price": [2.99, 3.49, 1.99, 4.99, 5.99, 6.99],
"weight": [250, 300, 200, 400, 500, 600],
}
)
figure: Figure = Figure(data=[Bar(name="Prix", x=data["product"], y=data["price"])])
figure.add_hrect(y0=2.75, y1=4.5, fillcolor="gray", opacity=0.25, layer="below")
figure.update_layout(
template="seaborn",
title="Prix et poids unitaires",
font={"family": "Cabin", "size": 13},
xaxis={"title": "Produit", "showgrid": False},
yaxis={"title": "Prix (€)", "showgrid": False}
)
figure.show(renderer="browser")