Python ile Veri Gorsellestirme: Plotly

Kurulum

pip install plotly dash pandas

Temel Grafikler

import plotly.graph_objects as go
import plotly.express as px
import pandas as pd

# Cizgi grafik
df = pd.DataFrame({'ay': range(1,13), 'satis': [120,145,132,168,175,190,210,198,215,230,248,270]})

fig = px.line(df, x='ay', y='satis',
    title='Aylik Satis', labels={'ay': 'Ay', 'satis': 'Satis (TL)'},
    markers=True, line_shape='spline',
    color_discrete_sequence=['#f97316'])

fig.update_layout(
    template='plotly_dark',
    plot_bgcolor='#0a0a0a',
    paper_bgcolor='#111',
    font_color='#ededed'
)

fig.show()
fig.write_html('grafik.html')

Sensor Veri Paneli

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

df = pd.read_csv('sensor_veri.csv')  # zaman,sicaklik,nem,basinc

fig = make_subplots(
    rows=3, cols=1,
    subplot_titles=['Sicaklik (C)', 'Nem (%)', 'Basinc (hPa)'],
    shared_xaxes=True
)

fig.add_trace(go.Scatter(x=df['zaman'], y=df['sicaklik'], fill='tonexty', line_color='#f97316'), row=1, col=1)
fig.add_trace(go.Scatter(x=df['zaman'], y=df['nem'],      fill='tonexty', line_color='#0ea5e9'), row=2, col=1)
fig.add_trace(go.Scatter(x=df['zaman'], y=df['basinc'],   fill='tonexty', line_color='#10b981'), row=3, col=1)

fig.update_layout(template='plotly_dark', showlegend=False, height=700)
fig.show()

Dash ile Canli Dashboard

from dash import Dash, dcc, html, Input, Output
import plotly.express as px

app = Dash(__name__)

app.layout = html.Div([
    html.H1('Sensor Dashboard'),
    dcc.Interval(id='interval', interval=5000),  # 5 saniyede bir guncelle
    dcc.Graph(id='grafik')
])

@app.callback(
    Output('grafik', 'figure'),
    Input('interval', 'n_intervals')
)
def guncelle(n):
    df = pd.read_csv('canli_veri.csv')  # Guncellenen dosya
    return px.line(df, x='zaman', y=['sicaklik', 'nem'])

if __name__ == '__main__':
    app.run(debug=True)

Plotly ve Dash, IoT veri gorselleştirme icin Python ekosisteminin en guclu ikili.