00:19:00	Christian Barreto:	https://wetransfer.com/downloads/3ae3d117b187e4bbd3bee277b475fea620210730183316/031862
00:20:28	Christian Barreto:	https://wetransfer.com/downloads/3ae3d117b187e4bbd3bee277b475fea620210730183316/031862
00:29:35	Christian Barreto:	https://wetransfer.com/downloads/3ae3d117b187e4bbd3bee277b475fea620210730183316/031862
00:30:20	Isabel Huayra-DZ11:	SI!
00:53:26	Christian Barreto:	********************
00:53:28	Christian Barreto:	# ejercicio para chuquibambilla

%reset -sf
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

file="Chuquibambilla_Puno.xlsx"
data=pd.read_excel(file)
data
00:55:10	Christian Barreto:	# columna a indice del dataframe
data_idx=data.set_index("FECHA")
data_idx
00:57:25	Christian Barreto:	ax=data_idx.plot(figsize=(14,3))
ax.axhline(data_idx.CHUQUIBAMBILLA.mean(),color="red",linestyle="dashed")
00:58:10	Christian Barreto:	ax=data_idx.plot(figsize=(14,3))
ax.axhline(data_idx.CHUQUIBAMBILLA.mean(),color="red",linestyle="dashed")
print("promedio de toda la data es:", data_idx.CHUQUIBAMBILLA.mean())
01:05:21	Christian Barreto:	ax=(data_idx - data_idx.CHUQUIBAMBILLA.mean()).plot(figsize=(14,3))
ax.axhline(data_idx.CHUQUIBAMBILLA.mean(),color="r",linestyle="dashed")
plt.savefig("datos_menos_todoelpromedio.png",dpi=300)
01:09:34	Christian Barreto:	# sacamos la media de cada mes

promedios=[]
desvest=[]

for i in np.arange(1,13,1):
    x=data_idx.loc[data_idx.index.month==i].mean()[0]
    dst=data_idx.loc[data_idx.index.month==i].std()[0]
    promedios.append(x)
    desvest.append(dst)
    
print(promedios)
print("--------")
print(desvest)
01:14:39	Christian Barreto:	data_idx.loc[data_idx.index.month==1]-promedios[0]
01:16:46	Christian Barreto:	data_anom=data_idx.copy()

for i in np.arange(1,13):
    data_anom.loc[data_anom.index.month==i]=data_idx.loc[data_idx.index.month==i]-promedios[i-1]
01:23:00	Christian Barreto:	data_anom.plot(figsize=(14,3))
plt.savefig("anomalias_chuqui.png",dpi =300)
01:24:49	Christian Barreto:	# anomalias vs anomalias STD
data_anom_std=data_anom.copy()

for i in np.arange(1,13):

    data_anom_std.loc[data_anom.index.month==i]=(data_idx.loc[data_idx.index.month==i]-promedios[i-1])/desvest[i-1]
01:28:31	Christian Barreto:	data_anom_std=data_anom_std.rename(columns={'Anom': 'Anom Est'})
data_anom_std
01:34:53	José Luis Ñiquen Sánchez DZ11:	la anterior sentencias también porfavor
01:35:49	Christian Barreto:	# concatenamos y comparamos
newdata = pd.concat([ data_anom, data_anom_std ],axis=1)
newdata.plot()
01:36:43	Christian Barreto:	# plot de comparacion anom vs anom std
plt.figure()
ax=newdata["Anom"].plot(style="k",figsize=(14,3),linewidth = 0.5)
ax2=newdata["Anom Est"].plot(secondary_y=True,style="g", linewidth=1, alpha=0.5)

ax.set_ylabel("pp anom")
ax.right_ax.set_ylabel("pp anom est")
ax.set_title("anom vs anom est")

ax.set_ylim(-150,150)
ax2.set_ylim(-6,6)

ax2.axhline(1,color="r",linestyle="solid")
ax2.axhline(-1,color="r",linestyle="solid")

plt.savefig("anom_vs_anom_est.png",dpi=300)
01:45:19	Christian Davila:	Christian, puedes volver a enviar los archivos de datos?
01:46:04	Christian Barreto:	https://wetransfer.com/downloads/3ae3d117b187e4bbd3bee277b475fea620210730183316/031862
01:46:13	Christian Davila:	Chévere, gracias
02:00:38	Christian Barreto:	# plot de comparacion anom vs anom std
plt.figure()
ax=newdata["Anom"].plot(style="k",figsize=(14,3),linewidth = 0.5)
ax2=newdata["Anom Est"].plot(secondary_y=True,style="g", linewidth=1, alpha=0.5)

ax.set_ylabel("pp anom")
ax.right_ax.set_ylabel("pp anom est")
ax.set_title("anom vs anom est")

ax.set_ylim(-150,150)
ax2.set_ylim(-6,6)

ax2.axhline(1,color="r",linestyle="solid")
ax2.axhline(-1,color="r",linestyle="solid")

plt.savefig("anom_vs_anom_est.png",dpi=300)
02:01:18	Christian Barreto:	christian.b.sch@gmail.com
02:08:28	Christian Barreto:	https://docs.google.com/spreadsheets/d/1V2KSk0qfBRliTknmHu_jHbHxa4U0Wou0gxhPvTeZ_cM/edit?usp=sharing
02:08:46	Kelita Quispe Vega:	sí se puede
02:10:12	Christian Barreto:	data_anom=data_anom.rename(columns={"CHUQUIBAMBILLA":"Anom"})
data_anom
02:19:37	Christian Barreto:	Hola
02:19:44	Christian Barreto:	descarga de datos y script asta el momento
02:19:45	Christian Barreto:	https://wetransfer.com/downloads/123ef008c556dbcd7f270b8ba5b4a1bf20210730231515/8e1381bafeeb0118c427f7e427790f1520210730231532/9722d3
02:27:20	Christian Barreto:	pip show xarray
02:27:57	Isabel Huayra-DZ11:	igual
02:28:28	Christian Barreto:	conda install -c anaconda xarray
02:30:42	Christian Barreto:	conda install -c conda-forge cartopy
02:30:46	Christian Barreto:	pip show cartopy
02:32:39	MARTÍN CAILLAHUA:	Ya está.
02:34:38	Christian Barreto:	import xarray as xr
02:35:46	Christian Barreto:	import xarray as xr
02:45:23	Lia Nicolle:	me sale error u.u
02:45:41	Christian Barreto:	import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import xarray as xr

dset = xr.open_dataset("precip.mon.mean.nc")
print(dset)
dset
02:47:13	Christian Barreto:	conda install dask netCDF4 bottleneck
02:51:30	Christian Davila:	!pip install geos
!pip install pyproj
!pip install cartopy

PARA COLAB
02:56:08	Christian Barreto:	conda install dask netCDF4 bottleneck
02:57:58	Stefany Amado Menauth DZ6:	me sale esto Christian
FileNotFoundError: [Errno 2] No such file or directory: b'C:\\Users\\stefa\\Documents\\CURSO T\xc3\x89CNICAS DE PRON\xc3\x93STICO SENAMHI\\precip.mon.mean.nc'
02:59:42	Stefany Amado Menauth DZ6:	ok, gracias
03:04:26	Christian Barreto:	*****************************************
03:07:41	Christian Barreto:	import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import xarray as xr

dset = xr.open_dataset("precip.mon.mean.nc")
print(dset)
dset
03:08:47	Christian Barreto:	pp=dset.precip
pp
03:08:59	Christian Barreto:	#first 1D plot, llamando por index
pp1d = pp.isel(lat=10, lon=10)
pp1d.plot()
03:11:21	Christian Barreto:	pp1d[:200].plot.line(color="purple", marker="o")
03:11:26	Christian Barreto:	pp.isel(lon=10, lat=[19, 21, 22]).plot.line(x="time")
03:13:12	Christian Barreto:	pp.isel(time=0).plot()
03:14:14	Christian Barreto:	pp.isel(time=0).plot(robust=True)
03:14:49	Christian Barreto:	#http://xarray.pydata.org/en/stable/user-guide/plotting.html
03:16:27	Christian Barreto:	pptrop=pp.sel(lat=slice(30,-30))
03:17:24	Christian Barreto:	pptrop=pp.sel(lat=slice(30,-30))
pptrop.sel(time="2010-01-01").plot(robust=True)
03:23:49	Christian Barreto:	# seleccionamos 1981-2010
pp_clim=pptrop.sel(time=slice("1981-01-01","2010-12-01")).groupby("time.month").mean(dim="time",skipna=True)
03:26:02	Christian Barreto:	pp_clim.sel(month=1).plot(robust=True)
plt.title("Enero Clim, 1981-2010")
03:27:54	Christian Barreto:	(pp_clim.sel(month=1)-pp_clim.sel(month=7)).plot(robust=True)
03:28:39	Christian Barreto:	(pp_clim.sel(month=1)-pp_clim.sel(month=7)).plot(robust=True)
03:30:44	Christian Barreto:	pp_suda=pp.sel(lat=slice(10, -60),lon=slice(250, 350))

#climatologia
pp_suda_c=pp_suda.sel(time=slice('1981-01-01', '2010-12-01')).groupby('time.month').mean(dim='time',skipna=True)

#anomalia en enero 1983
(pp_suda.sel(time="1983-01-01")-pp_suda_c.sel(month=1)).plot(robust=True,cbar_kwargs={"label": "mm/day"})
plt.title('Anomalia Enero 1983')
plt.savefig("pp_1983_anom.png",dpi=300)
03:32:16	Christian Barreto:	pp_suda=pp.sel(lat=slice(10, -60),lon=slice(250, 350))

#climatologia
pp_suda_c=pp_suda.sel(time=slice('1981-01-01', '2010-12-01')).groupby('time.month').mean(dim='time',skipna=True)

#anomalia en enero 1983
(pp_suda.sel(time="1983-01-01")-pp_suda_c.sel(month=1)).plot(robust=True,cbar_kwargs={"label": "mm/day"})
plt.title('Anomalia Enero 1983')
plt.savefig("pp_1983_anom.png",dpi=300)
03:33:34	Christian Barreto:	#SUBSET SUDAMERICA
pp_suda=pp.sel(lat=slice(10, -60),lon=slice(250, 350))

#climatologia
pp_suda_c=pp_suda.sel(time=slice('1981-01-01', '2010-12-01')).groupby('time.month').mean(dim='time',skipna=True)

#anomalia en enero 1999
(pp_suda.sel(time="1999-01-01")-pp_suda_c.sel(month=1)).plot(robust=True,cbar_kwargs={"label": "mm/day"})
plt.title('Anomalia Enero 1999')
03:34:18	Christian Barreto:	pp_suda=pp.sel(lat=slice(10, -60),lon=slice(250, 350))

#climatologia
pp_suda_c=pp_suda.sel(time=slice('1981-01-01', '2010-01-01')).groupby('time.month').mean(dim='time',skipna=True)

#desviacion estandar
pp_suda_std_c=pp_suda.sel(time=slice('1981-01-01', '2010-01-01')).groupby('time.month').std(dim='time',skipna=True)

##anomalia estandrixada en enero 1983
anom83=pp_suda.sel(time="1983-01-01")-pp_suda_c.sel(month=1)
anom83std=anom83/pp_suda_std_c.sel(month=1)
03:36:32	Christian Barreto:	************************
03:36:36	Christian Barreto:	pp_suda=pp.sel(lat=slice(10, -60),lon=slice(250, 350))

#climatologia
pp_suda_c=pp_suda.sel(time=slice('1981-01-01', '2010-12-01')).groupby('time.month').mean(dim='time',skipna=True)

#desviacion estandar
pp_suda_std_c=pp_suda.sel(time=slice('1981-01-01', '2010-12-01')).groupby('time.month').std(dim='time',skipna=True)

##anomalia estandrixada en enero 1983
anom83=pp_suda.sel(time="1983-01-01")-pp_suda_c.sel(month=1)
anom83std=anom83/pp_suda_std_c.sel(month=1)
03:36:40	Christian Barreto:	anom83std.plot(robust=True)
03:37:39	Christian Barreto:	anom83std.plot(robust=True)
plt.savefig("pp_1983_anom_1.png",dpi=300)
03:40:32	Christian Barreto:	import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from matplotlib import colorbar, colors
import cartopy.feature as cf
03:40:56	Christian Barreto:	# Draw coastlines of the Earth
ax = plt.axes(projection=ccrs.PlateCarree())
ax.add_feature(cf.BORDERS)
#ax.coastlines() 
ax.add_feature(cf.COASTLINE)
03:42:41	Christian Barreto:	# https://scitools.org.uk/cartopy/docs/latest/crs/projections.html
03:45:04	Christian Barreto:	******************************
03:45:12	Christian Barreto:	import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from matplotlib import colorbar, colors
import cartopy.feature as cf

# Draw coastlines of the Earth
ax = plt.axes(projection=ccrs.PlateCarree())
ax.add_feature(cf.BORDERS)
#ax.coastlines() 
ax.add_feature(cf.COASTLINE)

#adding ejes
xticks=([-120,-100,-80,-60,-40,-20,0])
yticks=([-75,-60,-45,-30,-15,0,15])
ax.set_xticks(xticks, crs=ccrs.PlateCarree())
ax.set_yticks(yticks, crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True,number_format='.1f')
lat_formatter = LatitudeFormatter(number_format='.1f')
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)

#adding grillas

ax.gridlines(draw_labels=False, xlocs=xticks, ylocs=yticks)

#plot data
levels=[-2.5,-2,-1,0,1,2,3]
clrs=["red","brown","peru","beige","skyblue","dodgerblue","purple","pink" ]
#anom83std.plot(levels=levels,colors=clrs,cbar_kwargs={"label": "anom. est. de pp (mm/day)"})
anom83std.plot
03:47:50	Christian Barreto:	********************************
03:47:52	Christian Barreto:	*****************************
03:48:01	Christian Barreto:	import cartopy.crs as ccrs
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from matplotlib import colorbar, colors
import cartopy.feature as cf

# Draw coastlines of the Earth
ax = plt.axes(projection=ccrs.PlateCarree())
ax.add_feature(cf.BORDERS)
#ax.coastlines() 
ax.add_feature(cf.COASTLINE)

#adding ejes
xticks=([-120,-100,-80,-60,-40,-20,0])
yticks=([-75,-60,-45,-30,-15,0,15])
ax.set_xticks(xticks, crs=ccrs.PlateCarree())
ax.set_yticks(yticks, crs=ccrs.PlateCarree())
lon_formatter = LongitudeFormatter(zero_direction_label=True,number_format='.1f')
lat_formatter = LatitudeFormatter(number_format='.1f')
ax.xaxis.set_major_formatter(lon_formatter)
ax.yaxis.set_major_formatter(lat_formatter)

#adding grillas

ax.gridlines(draw_labels=False, xlocs=xticks, ylocs=yticks)

#plot data
levels=[-2.5,-2,-1,0,1,2,3]
clrs=["red","brown","peru","beige","skyblue","dodgerblue","purple","pink" ]
#anom83std.plot(levels=levels,colors=clrs,cbar_kwargs={"label": "anom. est. de pp (mm/day)"})
anom83std.plot
03:48:22	Christian Barreto:	**************
03:48:23	Christian Barreto:	anom83std.plot.contourf(levels=levels,colors=clrs,cbar_kwargs={"label": "anom. est. de pp (mm/day)"})
plt.title('Anomalia Estandarizada de PP Enero 1983')
plt.xlabel('longitud')
plt.ylabel('latitud')

# tamaño correcto de barra
ax.set_aspect('auto', adjustable=None)
#plt.show()
#guarda figura
plt.savefig("pp_1983_anom_std_2.png",dpi=300)
03:56:13	Jorge Poma  Dz11:	Muchas gracias
03:56:18	Isabel Huayra-DZ11:	Gracias CHRISTIAN
03:57:27	Christian Barreto:	christian.b.sch@gmail.com