FEC_Visualiser_Trésorerie_Barline_Chart.ipynb

Kernel: Python 3

FEC - Visualiser Trésorerie Barline Chart

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Tags: #fec #plotly #naas #snippet #operations #barline

Author: Florent Ravenel

Last update: 2023-04-12 (Created: 2023-02-08)

Description: Ce notebook vous permettra de visualiser la trésorerie de votre entreprise à l'aide d'un diagramme de barres. Vous pourrez facilement suivre les entrées et les sorties d'argent, ce qui vous aidera à mieux comprendre la situation financière de votre entreprise.

Input

Import libraries

import plotly.graph_objects as go
from plotly.subplots import make_subplots
import pandas as pd
import naas
import random

Setup Variables

# Inputs
# Create sample financial data
data_cashin = {
    "ENTITY": ["Société X"] * 12,
    "SCENARIO": ["2022-12"] * 12,
    "LABEL": [
        "2022-01",
        "2022-02",
        "2022-03",
        "2022-04",
        "2022-05",
        "2022-06",
        "2022-07",
        "2022-08",
        "2022-09",
        "2022-10",
        "2022-11",
        "2022-12",
    ],
    "GROUP": ["Encaissements"] * 12,
    "VALUE": [random.randint(0, 1000) for i in range(0, 12)],
}
data_cashout = {
    "ENTITY": ["Société X"] * 12,
    "SCENARIO": ["2022-12"] * 12,
    "LABEL": [
        "2022-01",
        "2022-02",
        "2022-03",
        "2022-04",
        "2022-05",
        "2022-06",
        "2022-07",
        "2022-08",
        "2022-09",
        "2022-10",
        "2022-11",
        "2022-12",
    ],
    "GROUP": ["Décaissement"] * 12,
    "VALUE": [random.randint(0, 500) * -1 for i in range(0, 12)],
}

# Outputs
html_output = "Trésorerie_Barline.html"
png_output = "Trésorerie_Barline.png"

Model

Get "Cashin" data

df_cashin = pd.DataFrame(data_cashin)
df_cashin

Get "Cashout" data

df_cashout = pd.DataFrame(data_cashout)
df_cashout

Calculate "Cash Position"

# concat cash in and cash out
df_position = pd.concat([df_cashin, df_cashout])

# rename column GROUP = "Position" and groupby + agg
df_position["GROUP"] = "Trésorerie"
df_position = df_position.groupby(
    ["ENTITY", "SCENARIO", "LABEL", "GROUP"], as_index=False
).agg({"VALUE": "sum"})
df_position

Create barlinechart using Plotly

def create_barlinechart(
    df_cashin,
    df_cashout,
    df_position,
    xaxis_title=None,
    yaxis_title_r=None,
    yaxis_title_l=None,
):
    # Create figure with secondary y-axis
    fig = make_subplots(specs=[[{"secondary_y": True}]])

    # Add traces
    fig.add_trace(
        go.Bar(
            name="Encaissement",
            x=df_cashin["LABEL"],
            y=df_cashin["VALUE"],
            marker=dict(color="#1b7656"),
        ),
        secondary_y=False,
    )
    fig.add_trace(
        go.Bar(
            name="Décaissement",
            x=df_cashout["LABEL"],
            y=df_cashout["VALUE"] * -1,
            marker=dict(color="#cd3244"),
        ),
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            x=df_position["LABEL"],
            y=df_position["VALUE"],
            mode="lines",
            line=dict(color="#46a7f5", width=2.5),
        ),
        secondary_y=True,
    )

    # Add figure title
    fig.update_layout(
        title=f"Trésorerie Disponible : {df_position.loc[df_position.index[-1], 'VALUE']} €",
        title_font=dict(family="Arial", size=18, color="black"),
        legend=None,
        plot_bgcolor="#ffffff",
        width=1200,
        height=800,
        paper_bgcolor="white",
        xaxis_title=xaxis_title,
        xaxis_title_font=dict(family="Arial", size=12, color="black"),
        xaxis={"type": "category"},
    )

    # Set y-axes titles
    fig.update_yaxes(
        title_text=yaxis_title_r,
        title_font=dict(family="Arial", size=12, color="black"),
        secondary_y=False,
    )
    fig.update_yaxes(
        title_text=yaxis_title_l,
        title_font=dict(family="Arial", size=12, color="black"),
        secondary_y=True,
    )
    fig.update_traces(showlegend=False)
    fig.show()
    return fig


fig = create_barlinechart(
    df_cashin,
    df_cashout,
    df_position,
    xaxis_title="Mois",
    yaxis_title_r="Position",
    yaxis_title_l="Flux",
)

Output

Save and share your graph as PNG

fig.write_image(png_output)

# Share output with naas
naas.asset.add(png_output)

# -> Uncomment the line below to remove your asset
# naas.asset.delete(html_output)

Save and share your graph as HTML

fig.write_html(html_output)

# Share output with naas
naas.asset.add(html_output, params={"inline": True})

# -> Uncomment the line below to remove your asset
# naas.asset.delete(html_output)