From e0652f1efe80b50c82287fcb709d0f2858968001 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?David=20Hern=C3=A1ndez?= Date: Mon, 27 Apr 2020 05:50:12 -0400 Subject: [PATCH] =?UTF-8?q?Correcciones=20menores.=20Se=20cambia=20disposi?= =?UTF-8?q?ci=C3=B3n=20de=20gr=C3=A1ficas=20en=20los=20casos=20acumulados?= =?UTF-8?q?=20para=20una=20mejor=20visualizaci=C3=B3n?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 19 ++++++++------- corona-ve.py | 61 +++++++++++++++++++++++------------------------- images/fig1.png | Bin 93207 -> 97778 bytes images/fig2.png | Bin 46682 -> 49799 bytes images/fig3.png | Bin 75430 -> 87815 bytes images/fig4.png | Bin 39797 -> 42017 bytes images/fig5.png | Bin 31366 -> 33830 bytes 7 files changed, 39 insertions(+), 41 deletions(-) diff --git a/README.md b/README.md index cf474ac..444bc03 100644 --- a/README.md +++ b/README.md @@ -35,23 +35,24 @@ Script en Python para generación de gráficos referentes a los casos de COVID-1 Casos COVID-19 en Venezuela =========================== - Confirmados: 175 - Recuperados: 93 - Fallecidos: 9 - Activos: 73 + Confirmados: 325 + Recuperados: 137 + Fallecidos: 10 + Activos: 178 - Nuevos casos al 11/04/2020 + Nuevos casos al 26/04/2020 =========================== - Confirmados: 0 - Recuperados: 9 + Confirmados: 2 + Recuperados: 5 Fallecidos: 0 Estadísticas =========================== - Mortalidad: 5.14% - Recuperación: 53.14% + Letalidad: 3.08% + Recuperación: 42.15% ---- Datos adquiridos desde https://covid19.patria.org.ve/api-covid-19-venezuela/ + diff --git a/corona-ve.py b/corona-ve.py index 116e619..dc33022 100755 --- a/corona-ve.py +++ b/corona-ve.py @@ -4,7 +4,7 @@ """ Visualización del Corona Virus en Venezuela utilizando el API de https://covid19.patria.org.ve/api-covid-19-venezuela/ -por David Hernandez APonte <@davidhdz> 2020 +por David Hernandez Aponte <@davidhdz> 2020 """ import seaborn as sns @@ -19,19 +19,15 @@ dims = (15, 8) # Patch para leyenda del gráfico de barras de Casos nuevos -l1 = mpatches.Patch(color='#2A5CFF', alpha=0.6, label='Confirmados') -l2 = mpatches.Patch(color='#FF9028', alpha=0.6, label='Recuperados') -l3 = mpatches.Patch(color='#3ED157', alpha=0.6, label='Activos') -l4 = mpatches.Patch(color='#EB2831', alpha=0.6, label='Fallecidos') +l1 = mpatches.Patch(color='C0', alpha=0.8, label='Confirmados') +l2 = mpatches.Patch(color='C1', alpha=0.8, label='Recuperados') +l3 = mpatches.Patch(color='C2', alpha=0.8, label='Activos') +l4 = mpatches.Patch(color='C3', alpha=0.8, label='Fallecidos') # Personalización general de los gráficos sns.set_style("darkgrid") sns.set_palette("bright") -# Variables para el gráfico de distribución de casos por género -colors = ['#2A5CFF99', '#FF902899'] -explode = (0.1, 0) - # Función para añadir valores encima de las barras def show_values_on_bars(axs): @@ -90,34 +86,38 @@ def _show_on_single_plot(ax): confirmed_lines = sns.lineplot( x="Date", y="Count", - alpha=0.6, + alpha=0.8, markers=True, marker="o", - data=confirmados + data=confirmados, + label='Confirmados' ) recovered_lines = sns.lineplot( x="Date", y="Count", - alpha=0.6, + alpha=0.8, markers=True, marker="o", - data=recuperados + data=recuperados, + label='Recuperados' ) actives_lines = sns.lineplot( x="Date", y="Count", - alpha=0.6, + alpha=0.8, markers=True, marker="o", - data=activos + data=activos, + label='Activos' ) deaths_lines = sns.lineplot( x="Date", y="Count", - alpha=0.6, + alpha=0.8, markers=True, marker="o", - data=fallecidos + data=fallecidos, + label='Fallecidos' ) plt.xlabel("", fontsize=12, weight='bold') @@ -126,8 +126,6 @@ def _show_on_single_plot(ax): fontsize=15, weight='bold') confirmed_lines.xaxis.set_major_locator(mdates.DayLocator(interval=1)) confirmed_lines.figure.autofmt_xdate() - fig1.legend(labels=['Confirmados', 'Recuperados', 'Activos', - 'Fallecidos'], frameon=False, loc='upper center', ncol=4) fig1.savefig("fig1.png") @@ -136,7 +134,7 @@ def _show_on_single_plot(ax): fig2 = plt.figure(figsize=dims) new_cases = sns.barplot(x="Date", y="vals", hue="cols", - data=df_nuevos, alpha=0.6, palette=["C0", "C1", "C3"], dodge=True) + data=df_nuevos, alpha=0.8, palette=["C0", "C1", "C3"], dodge=True) new_cases.figure.autofmt_xdate(rotation='90', ha="center") show_values_on_bars(new_cases) @@ -150,23 +148,23 @@ def _show_on_single_plot(ax): # Gráfico de casos en Venezuela - fig3, axes = plt.subplots(2, 2, figsize=dims, sharex=True, sharey=True) + fig3, axes = plt.subplots(4, figsize=dims, sharex=True, sharey=True) confirmed_bars = sns.barplot( - x="Date", y="Count", data=confirmados, color="#2A5CFF", alpha=0.6, ax=axes[0, 0]) + x="Date", y="Count", data=confirmados, color="C0", alpha=0.8, ax=axes[0]) recovered_bars = sns.barplot( - x="Date", y="Count", data=recuperados, color="#FF9028", alpha=0.6, ax=axes[0, 1]) + x="Date", y="Count", data=recuperados, color="C1", alpha=0.8, ax=axes[1]) actives_bars = sns.barplot( - x="Date", y="Count", data=activos, color="#3ED157", alpha=0.6, ax=axes[1, 0]) + x="Date", y="Count", data=activos, color="C2", alpha=0.8, ax=axes[2]) deaths_bars = sns.barplot( - x="Date", y="Count", data=fallecidos, color="#EB2831", alpha=0.6, ax=axes[1, 1]) + x="Date", y="Count", data=fallecidos, color="C3", alpha=0.8, ax=axes[3]) show_values_on_bars(axes) confirmed_bars.set(xlabel='', ylabel='Cantidad de casos') - recovered_bars.set(xlabel='', ylabel='') + recovered_bars.set(xlabel='', ylabel='Cantidad de casos') actives_bars.set(xlabel='', ylabel='Cantidad de casos') - deaths_bars.set(xlabel='', ylabel='') - plt.suptitle('Casos de COVID-19 en Venezuela (acumulados por día)', + deaths_bars.set(xlabel='', ylabel='Cantidad de casos') + plt.suptitle('Casos de COVID-19 en Venezuela (acumulados)', fontsize=15, weight='bold') actives_bars.figure.autofmt_xdate(rotation='90', ha='center') fig3.legend(handles=[l1, l2, l3, l4], frameon=False, @@ -178,7 +176,7 @@ def _show_on_single_plot(ax): # Gráfico de distribución por género de casos en Venezuela fig4, ax4 = plt.subplots(figsize=dims) - ax4.pie(count_gender, labels=labels_gender, colors=colors, + ax4.pie(count_gender, labels=labels_gender, colors=['C0', 'C1'], wedgeprops={'alpha':0.8}, autopct=lambda p: '{:.0f}'.format(p * int(summary.Confirmed['Count']) / 100), shadow=False, startangle=90) centre_circle = plt.Circle((0, 0), 0.7, fc='white') @@ -195,10 +193,10 @@ def _show_on_single_plot(ax): # Gráfico de distribución por edades de casos en Venezuela fig5, ax5 = plt.subplots(figsize=dims) - gender_bars = sns.barplot(x="Range", y="Count", data=df_ages, alpha=0.6) + gender_bars = sns.barplot(x="Range", y="Count", data=df_ages, alpha=0.8) show_values_on_bars(gender_bars) - plt.xlabel("", fontsize=12, weight='bold') + plt.xlabel("Rango de edad", fontsize=12, weight='bold') plt.ylabel("Cantidad de casos", fontsize=12, weight='bold') plt.title("Distribución de casos por edad", fontsize=15, weight='bold') @@ -227,6 +225,5 @@ def _show_on_single_plot(ax): print("Recuperación: \t{0:3.2f}%".format((int(summary.Recovered['Count'])/int(summary.Confirmed['Count']))*100)) print() - 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