Variables

Variables numéricas

Resumen numérico

datos.describe()

	Edad	Peso	Altura	Max_BPM	Avg_BPM	Rep_BPM	Duracion	Calorias	Grasa	Agua	Frecuencia	IMC
count	973.000000	973.000000	973.00000	973.000000	973.000000	973.000000	973.000000	973.000000	973.000000	973.000000	973.000000	973.000000
mean	38.683453	73.854676	1.72258	179.883864	143.766701	62.223022	1.256423	905.422405	24.976773	2.626619	3.321686	24.912127
std	12.180928	21.207500	0.12772	11.525686	14.345101	7.327060	0.343033	272.641516	6.259419	0.600172	0.913047	6.660879
min	18.000000	40.000000	1.50000	160.000000	120.000000	50.000000	0.500000	303.000000	10.000000	1.500000	2.000000	12.320000
25%	28.000000	58.100000	1.62000	170.000000	131.000000	56.000000	1.040000	720.000000	21.300000	2.200000	3.000000	20.110000
50%	40.000000	70.000000	1.71000	180.000000	143.000000	62.000000	1.260000	893.000000	26.200000	2.600000	3.000000	24.160000
75%	49.000000	86.000000	1.80000	190.000000	156.000000	68.000000	1.460000	1076.000000	29.300000	3.100000	4.000000	28.560000
max	59.000000	129.900000	2.00000	199.000000	169.000000	74.000000	2.000000	1783.000000	35.000000	3.700000	5.000000	49.840000

Histogramas

datos_numericos = datos.select_dtypes("number")

for var in datos_numericos.columns:
  fig = go.Figure()
  no_plot = fig.add_trace(
    go.Histogram(x = datos.loc[:, var])
  )
  no_plot = fig.update_traces(marker_line_width = 1, marker_line_color = "white")
  fig.update_layout(title = var)
  fig.show()

Variables categóricas

datos_categoricos = datos.select_dtypes("object")

for var in datos_categoricos.columns:
  aux = datos_categoricos.loc[:, var].value_counts()
  
  fig = go.Figure()
  no_plot = fig.add_trace(
    go.Bar(x = aux.index, y = aux.to_list())
  )
  fig.update_layout(title = var)
  fig.show()