00:49:54	Andrés Rodríguez Flores:	Gracias!
00:53:14	Christian Barreto:	*---------------------
00:53:16	Christian Barreto:	#cargar datos de chuquibambilla

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

file="Chuquibambilla_Puno.xlsx"

data=pd.read_excel(file)

data
00:55:24	Christian Barreto:	data_idx=data.set_index("FECHA")

#seleccionamos mes =2, FEB

data_feb=data_idx.loc[data_idx.index.month==2]
00:57:44	Christian Barreto:	# seleccionar 1981-2010
data_feb_c=data_feb.loc["1981":"2010"]
data_feb_c
00:58:22	Christian Barreto:	data_feb_c.plot(marker="o")
01:00:13	Christian Barreto:	data_feb_c.sample(n=30,replace=True).plot(marker="o")
01:06:24	Christian Barreto:	promedios=[]

for i in range(1,1000):
    a=data_feb_c.sample(n=30,replace=True).mean()[0]
    promedios.append(a)

type(promedios)
01:10:15	Andrés Rodríguez Flores:	Cristian que es lo que hace el "replace(true)"?
01:11:23	Christian Barreto:	plt.hist(promedios)

plt.axvline(np.percentile(promedios,2.5),color="g",linestyle="dashed",linewidth=2)
plt.axvline(np.percentile(promedios,97.5),color="g",linestyle="dashed", linewidth=2)

print("promedio sin btstrp: ",data_feb_c.CHUQUIBAMBILLA.mean())
print("promedio con btstrp: ",np.mean(promedios))
print("Int. de confianza al 95%: ",np.percentile(promedios,2.5),"-",np.percentile(promedios,97.5))
01:36:56	Christian Barreto:	*******************************
01:37:06	Christian Barreto:	%reset -sf
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

file="otrasestaciones.xlsx"
data=pd.read_excel(file)
data_idx=data.set_index('FECHA')

data_idx=data_idx["HUANUCO"]
data_idx

print(type(data_idx))
01:37:16	Christian Barreto:	#seleccionar mes = 4
data_apr=data_idx.loc[data_idx.index.month==4]
data_apr_c=data_apr.loc["1981":"2010"]

print(type(data_apr_c))

data_apr_c
01:37:22	Christian Barreto:	promedios=[]
series=[]
for i in range(1,1000): # 5 no cuenta
    a=data_apr_c.sample(n=30,replace=True).mean()
    promedios.append(a)
    series.append(a)
02:20:11	Christian Barreto:	******************************************
02:20:14	Christian Barreto:	*******************************************************************
02:20:36	Christian Barreto:	pip install -U seaborn
02:22:16	Christian Barreto:	%reset -sf
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#pip install -U seaborn
file="Chuquibambilla_Puno.xlsx"
data=pd.read_excel(file)
data
02:24:00	Christian Barreto:	sns.histplot(data,stat="probability")
02:24:01	José Luis Ñiquen Sánchez DZ11:	por favor puede compartir los comandos anteriores, se me fue el internet
02:24:10	Christian Barreto:	**************************************
02:24:11	Christian Barreto:	*
02:24:18	Christian Barreto:	%reset -sf
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
#pip install -U seaborn
file="Chuquibambilla_Puno.xlsx"
data=pd.read_excel(file)
data
02:24:24	Christian Barreto:	sns.histplot(data,stat="probability") # density, count, frequency
02:24:42	Christian Barreto:	pip install -U seaborn
02:29:06	Christian Barreto:	#--------------
02:29:11	Christian Barreto:	#en febrero
data_idx=data.set_index('FECHA')
data_feb=data_idx.loc[data_idx.index.month==2]
sns.histplot(data_feb,stat="probability",bins=10) # density, frequency, count, probability
02:30:27	Christian Barreto:	#en julio
data_idx=data.set_index('FECHA')
data_jul=data_idx.loc[data_idx.index.month==7]
sns.histplot(data_jul,stat="probability",bins=10) # density, frequency, count, probability
02:36:07	Christian Barreto:	# plotear junto con el KDE (Kernel density smoothing)
ax=sns.histplot(data_feb,stat="probability",kde=True)
ax.set_title("histograma Enero chuquibambilla")
02:36:44	Christian Barreto:	#------------------
02:36:45	Christian Barreto:	sns.histplot(data_feb,stat="probability",bins=[0,25,50,75,100,125,150,175,200,225,250])
02:39:50	Christian Barreto:	#CDF empirical

sns.histplot(data_feb,bins=10,kde=True,cumulative=True,stat="probability")
02:41:05	Christian Barreto:	#solo KDE
sns.displot(data_feb,kind="kde")
02:41:37	Christian Barreto:	sns.displot(data_feb,kind="kde",cumulative=True)
02:58:00	Christian Barreto:	#################################
02:58:02	Christian Barreto:	d1=data_feb.loc["1961":"1990"]
d3=data_feb.loc["1981":"2010"]

d1=d1.rename(columns={"CHUQUIBAMBILLA":"61-90"})
d3=d3.rename(columns={"CHUQUIBAMBILLA":"81-10"})

newdata = pd.concat([d1,d3], axis=1)

sns.histplot(newdata,stat="probability",kde=True,bins=[0,25,50,75,100,125,150,175,200,225,250])
plt.axvline(d1.median()[0],color="blue")
plt.axvline(d1.quantile(0.95)[0],color="blue",linestyle="dashed")
plt.axvline(d1.quantile(0.05)[0],color="blue",linestyle="dashed")

plt.axvline(d3.median()[0],color="orange")
plt.axvline(d3.quantile(0.95)[0],color="orange",linestyle="dashed")
plt.axvline(d3.quantile(0.05)[0],color="orange",linestyle="dashed")
03:53:37	Christian Barreto:	https://docs.google.com/spreadsheets/d/1V2KSk0qfBRliTknmHu_jHbHxa4U0Wou0gxhPvTeZ_cM/edit#gid=0