Exemple #1
0
import dash_table
import dash_html_components as html
import dash_core_components as dcc
from make_figures import make_map, make_timeplot, FIRST_LINE_HEIGHT
from data_input import tidy_most_recent, get_all_data

if 'DEBUG' in os.environ:
    debug = os.environ['DEBUG'] == 'True'
    print(f"DEBUG environment variable present, DEBUG set to {debug}")
else:
    print("No DEBUG environment variable: defaulting to debug mode")
    debug = True

# -------- Data --------------------------
df, df_prediction = get_all_data()
df_tidy = tidy_most_recent(
    df)  # most recent date, tidy format (one column for countries)
df_tidy_table = df_tidy[['country_region',
                         'value']]  # keep only two columns for Dash DataTable

# ----------- Figures ---------------------
fig1 = make_map(df_tidy)
fig2 = make_timeplot(df, df_prediction)

# ------------ Markdown text ---------------
# maybe later we can break the text in several parts
with open("text_block.md", "r") as f:
    intro_md = f.read()

# -----------App definition-----------------------
app = dash.Dash(
    __name__,
Exemple #2
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    fig.update_layout(
        showlegend=True,
        annotations=[fatalities_annotation,
                     confirmed_annotation,
                     drag_handle_annotation],
        xaxis_tickfont_size=LABEL_FONT_SIZE - 4,
        yaxis_tickfont_size=LABEL_FONT_SIZE - 4,
        yaxis_type='linear',
        height=FIRST_LINE_HEIGHT,
        margin=dict(t=0, b=0.02),
        # The legend position + font size
        # See https://plot.ly/python/legend/#style-legend
        legend=dict(x=.05, y=.8, font_size=LABEL_FONT_SIZE)
    )



    return fig


if __name__ == '__main__':
    from data_input import get_all_data, tidy_most_recent

    df, df_prediction = get_all_data()
    # most recent date, tidy format (one column for countries)
    df_tidy = tidy_most_recent(df)
    df_tidy_fatalities = tidy_most_recent(df, 'death')

    fig1 = make_map(df_tidy, df_tidy_fatalities)
    fig2 = make_timeplot(df, df_prediction)
                y=1.05,
                yanchor="top",
                font_color='black',
            ),
        ],
        xaxis_tickfont_size=LABEL_FONT_SIZE - 4,
        yaxis_tickfont_size=LABEL_FONT_SIZE - 4,
        height=FIRST_LINE_HEIGHT,
        margin=dict(t=0, b=0.02),
        # The legend position + font size
        # See https://plot.ly/python/legend/#style-legend
        legend=dict(x=.05,
                    y=.8,
                    font_size=LABEL_FONT_SIZE,
                    title="Active cases in"),
    )
    return fig


if __name__ == '__main__':
    from data_input import get_all_data, tidy_most_recent

    df, df_prediction = get_all_data()
    # most recent date, tidy format (one column for countries)
    df_tidy = tidy_most_recent(df)
    df_tidy_fatalities = tidy_most_recent(df, 'death')
    df_tidy_recovered = tidy_most_recent(df, 'recovered')

    fig1 = make_map(df_tidy, df_tidy_fatalities, df_tidy_recovered)
    fig2 = make_timeplot(df, df_prediction)
Exemple #4
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                ),
                dict(
                    args=["yaxis", {'type':'linear'}],
                    label="lin",
                    method="relayout",
                ),

            ]),
            pad={"r": 10, "t": 10, "b":5},
            showactive=True,
            x=0.05,
            xanchor="left",
            y=1.35,
            yanchor="top",
            font_color='black',
        ),
    ],
    height=.9*FIRST_LINE_HEIGHT,
)

    return fig


if __name__ == '__main__':
    from data_input import get_all_data, tidy_most_recent
    df, df_prediction = get_all_data()
    df_tidy = tidy_most_recent(df)
    fig1 = make_map(df_tidy)
    fig2 = make_timeplot(df, df_prediction)