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1.py
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1.py
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import pandas as pd
import numpy as np
import time
from urllib.request import urlopen
def number_of_region(x):
S = [24, 25, 5, 6, 27, 23, 26, 7, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 8, 9, 10, 1, 3, 2, 4]
return S[x - 1]
def get_state_name(id):
if (id == 1):
state = 'Vinnitska'
return state
elif (id == 2):
state = 'Volynska'
return state
elif (id == 3):
state = 'Dniprovska'
return state
elif (id == 4):
state = 'Donetska'
return state
elif (id == 5):
state = 'Zhytomyrska'
return state
elif (id == 6):
state = 'Zakarpatska'
return state
elif (id == 7):
state = 'Zaporozhska'
return state
elif (id == 8):
state = 'Ivano-Frankivska'
return state
elif (id == 9):
state = 'Kyivska'
return state
elif (id == 10):
state = 'Kirovogradska'
return state
elif (id == 11):
state = 'Luganskska'
return state
elif (id == 12):
state = 'Lvivska'
return state
elif (id == 13):
state = 'Nikolaevska'
return state
elif (id == 14):
state = 'Odessaska'
return state
elif (id == 15):
state = 'Poltavaska'
return state
elif (id == 16):
state = 'Rivnenska'
return state
elif (id == 17):
state = 'Sumska'
return state
elif (id == 18):
state = 'Ternopilska'
return state
elif (id == 19):
state = 'Kharkovska'
return state
elif (id == 20):
state = 'Khersonska'
return state
elif (id == 21):
state = 'Khmelnytska'
return state
elif (id == 22):
state = 'Cherkaska'
return state
elif (id == 23):
state = 'Chernivetska'
return state
elif (id == 24):
state = 'Chernihivska'
return state
elif (id == 25):
state = 'Republic of Crimea'
return state
def name_with_time(index):
strtime = time.strftime("%Hh%Mm%Ss")
strdate = time.strftime("%d-%m-%Y")
name = get_state_name(index)
id = str(index)
file_name = id + '_' + name + strdate + strtime + '.csv'
return file_name
def save_all(id):
print(id)
filename = name(id)
appropriate_id = number_of_region(id)
url2 = r"https://www.star.nesdis.noaa.gov/smcd/emb/vci/VH/get_provinceData.php?country=UKR&provinceID=%s&year1=1990&year2=2000&type=Mean" % appropriate_id
vhi_url2 = urlopen(url2)
out2 = open(r"rawdata1/%s" % filename, 'wb')
out2.write(vhi_url2.read())
out2.close()
print("Step 1")
col = ['Year', 'Week', 'SMN', 'SMT', 'VCI', 'TCI', 'VHI']
df = pd.read_csv(r"rawdata1/%s" % filename, index_col=False, header=1, sep=", {0,3}|\s+", engine='python')
df.columns = col
df1 = df.drop(df.index[549])
print("Step 2")
url1 = r"https://www.star.nesdis.noaa.gov/smcd/emb/vci/VH/get_provinceData.php?country=UKR&provinceID=%s&year1=1990&year2=2000&type=VHI_Parea" % appropriate_id
vhi_url1 = urlopen(url1)
out1 = open(r"rawdata2/%s" % filename, 'wb')
out1.write(vhi_url1.read())
out1.close()
print("Step 3")
col = ['Year', 'Week', '0', '5', '10', '15', '20','25','30','35','40','45','50','55','60','65','70','75','80','85','90','95','100',]
df = pd.read_csv(r"rawdata2/%s" % filename, index_col=False, header=1, sep=", {0,3}|\s+", engine='python')
df.columns = col
df2 = df.drop(df.index[549])
print("Step 4")
df2 = df2.drop(['Year' , 'Week'],axis = 1)
frames = [ df1 ,df2 ]
result = pd.concat(frames, axis=1)
result.to_csv(r"freshdata/%s" % filename)
print("Step 5")
def name(index):
index_string = str(index)
filename = index_string + '_' + get_state_name(index) + '.csv'
return filename
def min_VHI(index):
filename = name(index)
df = pd.read_csv(r"freshdata/%s" % filename)
print("\nMin for " + get_state_name(index) + " : " + str(df['VHI'].min()))
def max_VHI(index):
filename= name(index)
df = pd.read_csv(r"freshdata/%s" % filename)
print("\nMax for " + get_state_name(index) + " : " + str(df['VHI'].max()))
def VHI_drought1(index):
filename = name(index)
df = pd.read_csv(r"freshdata/%s" % filename)
df=df[(df['VHI']<15)]
print('\nDrought in '+get_state_name(index))
print (df[['Year','Week','VHI']])
def VHI_drought2(index,area):
filename = name(index)
df = pd.read_csv(r"freshdata/%s" % filename)
sum_rows = pd.DataFrame(np.zeros((549, 1)))
for i in range(0,3):
n = i*5
result = pd.concat([sum_rows,df[r"%s" % n]],axis=1)
sum_rows = result.sum(axis=1)
df['VHI<15'] = sum_rows
print(df[df['VHI<15']>area][['Year','VHI']])
for index in range(1,26):
save_all(index)
min_VHI(index)
max_VHI(index)
VHI_drought1(index)
VHI_drought2(index,50)