Diagrama de caja - Construction of BoxPlot and Basic Stats with Python - Pandas

# # Construction of BoxPlot and Basic Stats with Python

Bienvenidos nuevamente!

Adjunto a ustedes el código de explicación de funciones básicas en Python (Pandas, Numpy) utilizando el Jupyter Notebook. Aquí encontrarán uso de media, moda, mediana y rango intercuartílico así como gráficos importantes en la exploración de los datos como ser Diagrama de cajas (BoxPlot) e histogramas.

Igualmente, les adjunto de manera insertada el vídeo de dicha explicación.
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import pandas as pd
from pandas import read_csv
from scipy import stats
datosNB = pd.read_csv('Documents/Canal Yout/Stats with Python/birth2011.csv',sep=',')



datosNB = datosNB.sample(n=500)
datosNB.head()

DOB_MM	DOB_WK	OCNTY	MAGER	MRCNTY	FAGECOMB	DWGT	DMETH_REC	APGAR5	SEX	COMBGEST	DBWT
0	1	7	127	24	999	25.0	160	1	9	M	38	3090
1	1	7	25	19	25	21.0	143	1	9	F	39	3062
2	1	1	999	25	999	45.0	172	1	10	F	39	3062
3	1	3	25	38	25	32.0	192	2	9	F	39	3062
4	1	2	999	23	999	25.0	194	1	9	M	39	3941

# # Select groups


df1 = datosNB.DBWT[datosNB.SEX=='M']
df2 = datosNB.DBWT[datosNB.SEX=='F']


print("Mean for M", df1.mean() )
print("Std for M", df1.std() )
print("Mean for F", df2.mean() )
print("Std for F", df2.std() )


df1.median()

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import numpy as np
np.max(df1)


np.min(df1)



df1.quantile ()   #  print median only
q1,q2,q3 = df1.quantile([0.25,0.5,0.75])
print("Cuartiles: ")
print( "Q1 ", q1)
print( "Q2 (mediana) ", q2)
print( "Q3 ",q3)



#Rango intercuartilico para Masculino
RIC = q3 -q1
L1 = q1 - 1.5*RIC
L2 = q3 + 1.5*RIC

# todo numero considerado no outlier o valor extremo
print("L1: ", L1, " hasta L2:", L2)


import matplotlib
matplotlib.style.use('ggplot')

import matplotlib.pyplot as plt
get_ipython().magic('matplotlib inline')
import seaborn as sb

#sb.boxplot(x="SEX", y="DBWT", data=datosNB, palette="Set1")

sb.boxplot( y=df1, palette="Set1")


np.random.seed(1)
#plt.hist(df1)      # It is possible to let python to choose the number of bins

plt.hist(df1, bins=10, edgecolor='black')  #  range=(0,6000)
plt.show()

# # Number of weeks when newborn was born


datosNB.COMBGEST[ datosNB.DBWT== np.min(df1)]



np.ptp(df1)  # Range



moda = stats.mode(df1)
print("The modal value is {} with a count of {}".format(moda.mode[0], moda.count[0]))



plt.hist(datosNB.COMBGEST[datosNB.SEX=='M'] , bins=10, edgecolor='black')  #  range=(0,6000)
plt.show()



moda = stats.mode(datosNB.COMBGEST[datosNB.SEX=='M'])
print("The modal value is {} with a count of {}".format(moda.mode[0], moda.count[0]))