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In [1]:



    


import pandas as pd
import sys
import matplotlib



    











In [2]:



    


water23 = pd.read_csv("../data/waterlevel/Water23.csv", index_col='date')



    











In [3]:



    


%pylab inline



    


















    






Populating the interactive namespace from numpy and matplotlib

















In [4]:



    


climate = pd.read_csv("../data/waterlevel/ClimateWater.csv", index_col='date')



    











In [5]:



    


climate



    


















    
Out[5]:










  
    

      
      Temp(C)
      Rainfall(mm)
      Moisture(%)
      SurfaceTemp(surC)
      WaterH1
    

    

      date
      
      
      
      
      
    

  
  
    

      2015-01-01
      -3.9
      0.2
      62.9
      -1.8
      39.30
    

    

      2015-01-02
      -4.3
      2.4
      74.8
      -0.8
      39.34
    

    

      2015-01-03
      -1.1
      NaN
      69.4
      0.3
      39.34
    

    

      2015-01-04
      3.1
      NaN
      87.6
      2.6
      39.34
    

    

      2015-01-05
      5.5
      13.5
      77.4
      3.1
      39.42
    

    

      2015-01-06
      0.0
      2.5
      66.3
      1.9
      39.47
    

    

      2015-01-07
      -3.0
      NaN
      53.9
      -3.0
      39.53
    

    

      2015-01-08
      -2.3
      NaN
      73.0
      -1.9
      39.56
    

    

      2015-01-09
      0.4
      0.0
      80.9
      0.1
      39.59
    

    

      2015-01-10
      0.9
      NaN
      71.4
      0.1
      39.59
    

    

      2015-01-11
      2.5
      0.0
      61.0
      1.5
      39.59
    

    

      2015-01-12
      -1.8
      NaN
      52.8
      -1.1
      39.68
    

    

      2015-01-13
      0.8
      NaN
      57.4
      -0.3
      39.70
    

    

      2015-01-14
      3.3
      NaN
      61.3
      1.7
      39.72
    

    

      2015-01-15
      3.1
      NaN
      62.3
      2.8
      39.74
    

    

      2015-01-16
      3.3
      0.0
      74.0
      2.3
      39.76
    

    

      2015-01-17
      -1.3
      NaN
      60.5
      1.0
      39.76
    

    

      2015-01-18
      0.6
      2.0
      77.3
      -0.2
      39.76
    

    

      2015-01-19
      2.7
      0.3
      68.0
      2.4
      39.82
    

    

      2015-01-20
      0.4
      NaN
      71.3
      1.8
      39.84
    

    

      2015-01-21
      3.5
      5.0
      77.6
      2.3
      39.86
    

    

      2015-01-22
      2.5
      1.0
      89.1
      4.2
      39.89
    

    

      2015-01-23
      1.7
      NaN
      81.3
      2.2
      39.92
    

    

      2015-01-24
      3.5
      NaN
      78.6
      3.8
      39.92
    

    

      2015-01-25
      7.1
      2.5
      73.5
      4.1
      39.92
    

    

      2015-01-26
      5.6
      0.5
      94.5
      5.9
      39.97
    

    

      2015-01-27
      -1.0
      NaN
      65.4
      1.5
      40.00
    

    

      2015-01-28
      -2.8
      NaN
      58.9
      -1.6
      40.02
    

    

      2015-01-29
      0.5
      NaN
      65.4
      0.7
      40.04
    

    

      2015-01-30
      -0.8
      NaN
      63.9
      1.6
      40.06
    

    

      ...
      ...
      ...
      ...
      ...
      ...
    

    

      2015-12-02
      9.5
      11.6
      77.0
      7.5
      33.88
    

    

      2015-12-03
      4.0
      4.1
      66.0
      3.8
      33.99
    

    

      2015-12-04
      3.6
      5.5
      85.1
      3.4
      34.09
    

    

      2015-12-05
      6.6
      NaN
      67.9
      4.9
      34.18
    

    

      2015-12-06
      2.1
      NaN
      65.0
      3.7
      34.24
    

    

      2015-12-07
      2.5
      NaN
      65.5
      3.2
      34.29
    

    

      2015-12-08
      3.8
      NaN
      70.8
      3.7
      34.30
    

    

      2015-12-09
      7.6
      NaN
      71.8
      5.8
      34.40
    

    

      2015-12-10
      9.6
      9.7
      90.0
      8.1
      34.43
    

    

      2015-12-11
      7.7
      NaN
      79.0
      6.9
      34.50
    

    

      2015-12-12
      7.0
      NaN
      70.5
      5.5
      34.50
    

    

      2015-12-13
      8.6
      NaN
      64.9
      8.4
      34.57
    

    

      2015-12-14
      6.9
      6.9
      88.9
      6.8
      34.60
    

    

      2015-12-15
      7.0
      0.0
      78.4
      7.0
      34.60
    

    

      2015-12-16
      0.6
      19.5
      90.0
      1.7
      34.68
    

    

      2015-12-17
      -1.5
      0.0
      69.5
      2.3
      34.80
    

    

      2015-12-18
      0.1
      NaN
      86.8
      2.3
      34.80
    

    

      2015-12-19
      2.9
      NaN
      86.0
      3.6
      34.86
    

    

      2015-12-20
      3.0
      0.0
      80.5
      2.7
      34.90
    

    

      2015-12-21
      5.5
      0.5
      84.4
      6.4
      35.00
    

    

      2015-12-22
      3.6
      0.0
      86.3
      3.3
      35.00
    

    

      2015-12-23
      6.0
      0.0
      89.1
      6.9
      35.00
    

    

      2015-12-24
      3.8
      NaN
      76.3
      4.0
      35.10
    

    

      2015-12-25
      1.9
      0.0
      54.8
      2.5
      35.10
    

    

      2015-12-26
      6.4
      0.2
      68.9
      4.6
      35.10
    

    

      2015-12-27
      -2.1
      NaN
      62.9
      0.9
      35.20
    

    

      2015-12-28
      -1.4
      NaN
      67.1
      0.9
      35.20
    

    

      2015-12-29
      0.0
      NaN
      73.5
      0.4
      35.20
    

    

      2015-12-30
      3.0
      7.0
      78.3
      3.1
      35.30
    

    

      2015-12-31
      2.6
      NaN
      83.1
      2.9
      35.28
    

  



365 rows × 5 columns



















In [6]:



    


newindex = []
for ind in water23.index:
    newindex.append(ind.split()[0])



    











In [7]:



    


vals, inds = np.unique(newindex, return_inverse=True)



    











In [8]:



    


upperh_med = np.ones(vals.size)*np.nan
downh_med = np.ones(vals.size)*np.nan
upperh_std = np.ones(vals.size)*np.nan
downh_std = np.ones(vals.size)*np.nan

for i in range (vals.size):
    active = inds==i
    upperh_med[i] = np.median(water23["upperlevel"].values[active])
    downh_med[i] = np.median(water23["downlevel"].values[active])
    upperh_std[i] = np.std(water23["upperlevel"].values[active])
    downh_std[i] = np.std(water23["downlevel"].values[active])



    











In [9]:



    


date = climate.index.values



    











In [10]:



    


climate.keys()



    


















    
Out[10]:








Index([u'Temp(C)', u'Rainfall(mm)', u'Moisture(%)', u'SurfaceTemp(surC)',
       u'WaterH1'],
      dtype='object')

















In [11]:



    


actind = np.in1d(date, vals)



    











In [12]:



    


upperh = np.ones(date.size)*np.nan
downh = np.ones(date.size)*np.nan
upperh[actind] = upperh_med
downh[actind] = downh_med



    











In [15]:



    


waterdataset = list (zip(date, climate['WaterH1'].values, upperh, downh,\
                         climate['Rainfall(mm)'].values, climate['SurfaceTemp(surC)'].values, climate['Moisture(%)'].values))
df = pd.DataFrame(data = waterdataset, columns=['date', 'reservoirH', 'upperH_med', 'downH_med',\
                                                'Rainfall (mm)', 'Temp (degree)', 'Moisture (percent)'])
df.set_index('date')



    


















    
Out[15]:










  
    

      
      reservoirH
      upperH_med
      downH_med
      Rainfall (mm)
      Temp (degree)
      Moisture (percent)
    

    

      date
      
      
      
      
      
      
    

  
  
    

      2015-01-01
      39.30
      NaN
      NaN
      0.2
      -1.8
      62.9
    

    

      2015-01-02
      39.34
      NaN
      NaN
      2.4
      -0.8
      74.8
    

    

      2015-01-03
      39.34
      NaN
      NaN
      NaN
      0.3
      69.4
    

    

      2015-01-04
      39.34
      NaN
      NaN
      NaN
      2.6
      87.6
    

    

      2015-01-05
      39.42
      NaN
      NaN
      13.5
      3.1
      77.4
    

    

      2015-01-06
      39.47
      NaN
      NaN
      2.5
      1.9
      66.3
    

    

      2015-01-07
      39.53
      NaN
      NaN
      NaN
      -3.0
      53.9
    

    

      2015-01-08
      39.56
      NaN
      NaN
      NaN
      -1.9
      73.0
    

    

      2015-01-09
      39.59
      NaN
      NaN
      0.0
      0.1
      80.9
    

    

      2015-01-10
      39.59
      NaN
      NaN
      NaN
      0.1
      71.4
    

    

      2015-01-11
      39.59
      NaN
      NaN
      0.0
      1.5
      61.0
    

    

      2015-01-12
      39.68
      NaN
      NaN
      NaN
      -1.1
      52.8
    

    

      2015-01-13
      39.70
      NaN
      NaN
      NaN
      -0.3
      57.4
    

    

      2015-01-14
      39.72
      NaN
      NaN
      NaN
      1.7
      61.3
    

    

      2015-01-15
      39.74
      NaN
      NaN
      NaN
      2.8
      62.3
    

    

      2015-01-16
      39.76
      35.515
      19.750
      0.0
      2.3
      74.0
    

    

      2015-01-17
      39.76
      35.460
      20.345
      NaN
      1.0
      60.5
    

    

      2015-01-18
      39.76
      35.500
      20.480
      2.0
      -0.2
      77.3
    

    

      2015-01-19
      39.82
      35.550
      20.580
      0.3
      2.4
      68.0
    

    

      2015-01-20
      39.84
      35.525
      20.610
      NaN
      1.8
      71.3
    

    

      2015-01-21
      39.86
      35.585
      20.570
      5.0
      2.3
      77.6
    

    

      2015-01-22
      39.89
      35.640
      20.580
      1.0
      4.2
      89.1
    

    

      2015-01-23
      39.92
      35.630
      20.610
      NaN
      2.2
      81.3
    

    

      2015-01-24
      39.92
      35.640
      20.620
      NaN
      3.8
      78.6
    

    

      2015-01-25
      39.92
      35.660
      20.595
      2.5
      4.1
      73.5
    

    

      2015-01-26
      39.97
      35.720
      20.600
      0.5
      5.9
      94.5
    

    

      2015-01-27
      40.00
      35.700
      20.630
      NaN
      1.5
      65.4
    

    

      2015-01-28
      40.02
      35.685
      20.630
      NaN
      -1.6
      58.9
    

    

      2015-01-29
      40.04
      35.710
      20.600
      NaN
      0.7
      65.4
    

    

      2015-01-30
      40.06
      35.740
      20.610
      NaN
      1.6
      63.9
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      2015-12-02
      33.88
      NaN
      NaN
      11.6
      7.5
      77.0
    

    

      2015-12-03
      33.99
      NaN
      NaN
      4.1
      3.8
      66.0
    

    

      2015-12-04
      34.09
      NaN
      NaN
      5.5
      3.4
      85.1
    

    

      2015-12-05
      34.18
      NaN
      NaN
      NaN
      4.9
      67.9
    

    

      2015-12-06
      34.24
      NaN
      NaN
      NaN
      3.7
      65.0
    

    

      2015-12-07
      34.29
      NaN
      NaN
      NaN
      3.2
      65.5
    

    

      2015-12-08
      34.30
      NaN
      NaN
      NaN
      3.7
      70.8
    

    

      2015-12-09
      34.40
      NaN
      NaN
      NaN
      5.8
      71.8
    

    

      2015-12-10
      34.43
      NaN
      NaN
      9.7
      8.1
      90.0
    

    

      2015-12-11
      34.50
      NaN
      NaN
      NaN
      6.9
      79.0
    

    

      2015-12-12
      34.50
      NaN
      NaN
      NaN
      5.5
      70.5
    

    

      2015-12-13
      34.57
      NaN
      NaN
      NaN
      8.4
      64.9
    

    

      2015-12-14
      34.60
      NaN
      NaN
      6.9
      6.8
      88.9
    

    

      2015-12-15
      34.60
      NaN
      NaN
      0.0
      7.0
      78.4
    

    

      2015-12-16
      34.68
      NaN
      NaN
      19.5
      1.7
      90.0
    

    

      2015-12-17
      34.80
      NaN
      NaN
      0.0
      2.3
      69.5
    

    

      2015-12-18
      34.80
      NaN
      NaN
      NaN
      2.3
      86.8
    

    

      2015-12-19
      34.86
      NaN
      NaN
      NaN
      3.6
      86.0
    

    

      2015-12-20
      34.90
      NaN
      NaN
      0.0
      2.7
      80.5
    

    

      2015-12-21
      35.00
      NaN
      NaN
      0.5
      6.4
      84.4
    

    

      2015-12-22
      35.00
      NaN
      NaN
      0.0
      3.3
      86.3
    

    

      2015-12-23
      35.00
      NaN
      NaN
      0.0
      6.9
      89.1
    

    

      2015-12-24
      35.10
      NaN
      NaN
      NaN
      4.0
      76.3
    

    

      2015-12-25
      35.10
      NaN
      NaN
      0.0
      2.5
      54.8
    

    

      2015-12-26
      35.10
      NaN
      NaN
      0.2
      4.6
      68.9
    

    

      2015-12-27
      35.20
      NaN
      NaN
      NaN
      0.9
      62.9
    

    

      2015-12-28
      35.20
      NaN
      NaN
      NaN
      0.9
      67.1
    

    

      2015-12-29
      35.20
      NaN
      NaN
      NaN
      0.4
      73.5
    

    

      2015-12-30
      35.30
      NaN
      NaN
      7.0
      3.1
      78.3
    

    

      2015-12-31
      35.28
      NaN
      NaN
      NaN
      2.9
      83.1
    

  



365 rows × 6 columns



















In [16]:



    


df['upperH_med'].plot(figsize=(20,3),color='k')



    


















    
Out[16]:








<matplotlib.axes._subplots.AxesSubplot at 0x115774150>










    
























In [17]:



    


fig = plt.figure(figsize=(12,4))
ax1 = plt.subplot(111)
ax1_1 = ax1.twinx()
df['upperH_med'].plot(figsize=(20,3), ax=ax1, color='k')
df['reservoirH'].plot(figsize=(20,3), ax=ax1, color='b')
df['downH_med'].plot(figsize=(20,3), ax=ax1_1, color='r')
grid(True)



    


















    
























In [18]:



    


df.keys()



    


















    
Out[18]:








Index([u'date', u'reservoirH', u'upperH_med', u'downH_med', u'Rainfall (mm)',
       u'Temp (degree)', u'Moisture (percent)'],
      dtype='object')

















In [19]:



    


ax1 = plt.subplot(111)
ax1_1 = ax1.twinx()
df.plot(figsize=(12,3), x='date', y='reservoirH', ax=ax1, color='k', linestyle='-', lw=2, marker='.', ms=2)
df.plot(figsize=(12,3), x='date', y='upperH_med', ax=ax1, color='k', linestyle='--', lw=2)
df.plot(figsize=(12,3), x='date', y='downH_med', ax=ax1_1, color='r', linestyle='-')
ax1_1.legend(loc=4)
ax1.grid(True)
indst, indend = 80, 100
ax1.plot(np.r_[indst, indst], np.r_[28, 42], 'k-')
ax1.plot(np.r_[indend, indend], np.r_[28, 42], 'k--')
print df['date'].values[indst], df['date'].values[indst]
# ax1.set_ylim(39.5, 40.5)
# ax1.set_xlim(indst, indend)



    


















    






2015-03-22 2015-03-22










    
























In [20]:



    


ax1 = plt.subplot(111)
ax1_1 = ax1.twinx()
df.plot(figsize=(12,3), x='date', y='reservoirH', ax=ax1, color='k', linestyle='-', lw=2, marker='.', ms=2)
df.plot(figsize=(12,3), x='date', y='upperH_med', ax=ax1, color='k', linestyle='--', lw=2)
df.plot(figsize=(12,3), x='date', y='downH_med', ax=ax1_1, color='r', linestyle='-')
ax1_1.legend(loc=4)
ax1.grid(True)
indst, indend = 80, 100
ax1.plot(np.r_[indst, indst], np.r_[28, 42], 'k-')
ax1.plot(np.r_[indend, indend], np.r_[28, 42], 'k--')
print df['date'].values[indst], df['date'].values[indst]
ax1.set_ylim(39.5, 40.5)
ax1.set_xlim(indst, indend)



    


















    






2015-03-22 2015-03-22










    
Out[20]:








(80, 100)










    
























In [21]:



    


ax1 = plt.subplot(111)
df.plot(figsize=(12,3), x='date', y='Rainfall (mm)', ax=ax1, color='b', marker='o', linestyle="-", ms=3)
df.plot(figsize=(12,3), x='date', y='Temp (degree)', ax=ax1, color='k', marker='None', linestyle="-", ms=3)
plt.tight_layout()



    


















    
























In [22]:



    


import sys
sys.path.append("../codes/")

from Readfiles import getFnames
from DCdata import readReservoirDC_data, readReservoirDC_all

directory = "../data/ChungCheonDC/"
fnames = getFnames(directory, dtype="apr", minimumsize=7000.)



    











In [23]:



    


import datetime
import numpy as np



    











In [24]:



    


def getdate(fstring):
    temp = fstring.split('.')[0]
    return datetime.date(int(temp[:4]), int(temp[4:6]), int(temp[6:8]))



    











In [25]:



    


date_temp = getdate(fnames[20])



    











In [26]:



    


date_temp.strftime("%Y-%m-%d")



    


















    
Out[26]:








'2015-01-06'

















In [37]:



    


# for i in range (vals.size):
#     active = inds==i
#     upperh_med[i] = np.median(water23["upperlevel"].values[active])
#     downh_med[i] = np.median(water23["downlevel"].values[active])
#     upperh_std[i] = np.std(water23["upperlevel"].values[active])
#     downh_std[i] = np.std(water23["downlevel"].values[active])



    











In [45]:



    


dat_temp, htemp, ID = readReservoirDC_all(directory+fnames[0])
ID.append('date')
ID.append('fnames')
ntimes = len(fnames)
DATA = np.zeros((dat_temp.shape[0], ntimes))*np.nan
index = np.ones(ntimes, dtype='bool')
for i, fname in enumerate(fnames):
    dat_temp = readReservoirDC_data(directory+fname)
    if dat_temp.shape[0] == 380:        
        DATA[:,i] = dat_temp[:,-1]
    else:
        print fname,dat_temp.shape[0]
        index[i] = False



    


















    






20150103180000.apr 379
20150106180000.apr 379
20150109120000.apr 379
20150112120000.apr 379
20150117120000.apr 379
20150120120000.apr 379
20150123120000.apr 379
20150126120000.apr 379
20150127000000.apr 379
20150129060000.apr 379
20150201000000.apr 379
20150204000000.apr 379
20150207000000.apr 379
20150209180000.apr 379
20150212180000.apr 379
20150215180000.apr 379
20150218120000.apr 379
20150221060000.apr 379
20150224120000.apr 379
20150227060000.apr 379
20150228000000.apr 379
20150302000000.apr 379
20150305000000.apr 379
20150308000000.apr 379
20150329000000.apr 379
20150401000000.apr 379
20150403180000.apr 379
20150404120000.apr 379
20150406180000.apr 379
20150409000000.apr 379
20150412120000.apr 379
20150415060000.apr 379
20150418000000.apr 379
20150421000000.apr 379
20150424000000.apr 379

















In [70]:



    






    


















    
Out[70]:








382

















In [48]:



    


fnameDC = np.array(fnames)[index]
datesDC = []
for i in range(fnameDC.size):
    tempdate = getdate(fnameDC[i])
    datesDC.append(tempdate.strftime("%Y-%m-%d"))
datesDC = np.array(datesDC)



    











In [49]:



    


datesDC.size



    


















    
Out[49]:








1235

















In [51]:



    


vals, inds = np.unique(datesDC, return_inverse=True)



    











In [52]:



    


DATA_active = DATA[:,index]
DATA_DC = np.zeros((vals.size,DATA.shape[0]))*np.nan
DATA_DC_std = np.zeros((vals.size,DATA.shape[0]))*np.nan
for i in range (vals.size):
    active = inds==i
    DATA_DC[i,:] = np.median(DATA_active[:,active], axis=1)
    DATA_DC_std[i,:] = np.std(DATA_active[:,active], axis=1)



    











In [53]:



    


actind = np.in1d(date, vals)
DATA_DC_final = np.zeros((365,DATA.shape[0]))*np.nan
DATA_DC_std_final = np.zeros((365,DATA.shape[0]))*np.nan
DATA_DC_final[actind,:] = DATA_DC
DATA_DC_std_final[actind,:] = DATA_DC_std



    











In [54]:



    


DATA_DC_final.shape



    


















    
Out[54]:








(365, 380)

















In [56]:



    


date.shape



    


















    
Out[56]:








(365,)

















In [57]:



    


DATA_DC_std_final.shape



    


















    
Out[57]:








(365, 380)

















In [58]:



    


date.reshape([-1,1]).shape



    


















    
Out[58]:








(365, 1)

















In [63]:



    


len(ID)



    


















    
Out[63]:








382

















In [66]:



    


date



    


















    
Out[66]:








array(['2015-01-01', '2015-01-02', '2015-01-03', '2015-01-04',
       '2015-01-05', '2015-01-06', '2015-01-07', '2015-01-08',
       '2015-01-09', '2015-01-10', '2015-01-11', '2015-01-12',
       '2015-01-13', '2015-01-14', '2015-01-15', '2015-01-16',
       '2015-01-17', '2015-01-18', '2015-01-19', '2015-01-20',
       '2015-01-21', '2015-01-22', '2015-01-23', '2015-01-24',
       '2015-01-25', '2015-01-26', '2015-01-27', '2015-01-28',
       '2015-01-29', '2015-01-30', '2015-01-31', '2015-02-01',
       '2015-02-02', '2015-02-03', '2015-02-04', '2015-02-05',
       '2015-02-06', '2015-02-07', '2015-02-08', '2015-02-09',
       '2015-02-10', '2015-02-11', '2015-02-12', '2015-02-13',
       '2015-02-14', '2015-02-15', '2015-02-16', '2015-02-17',
       '2015-02-18', '2015-02-19', '2015-02-20', '2015-02-21',
       '2015-02-22', '2015-02-23', '2015-02-24', '2015-02-25',
       '2015-02-26', '2015-02-27', '2015-02-28', '2015-03-01',
       '2015-03-02', '2015-03-03', '2015-03-04', '2015-03-05',
       '2015-03-06', '2015-03-07', '2015-03-08', '2015-03-09',
       '2015-03-10', '2015-03-11', '2015-03-12', '2015-03-13',
       '2015-03-14', '2015-03-15', '2015-03-16', '2015-03-17',
       '2015-03-18', '2015-03-19', '2015-03-20', '2015-03-21',
       '2015-03-22', '2015-03-23', '2015-03-24', '2015-03-25',
       '2015-03-26', '2015-03-27', '2015-03-28', '2015-03-29',
       '2015-03-30', '2015-03-31', '2015-04-01', '2015-04-02',
       '2015-04-03', '2015-04-04', '2015-04-05', '2015-04-06',
       '2015-04-07', '2015-04-08', '2015-04-09', '2015-04-10',
       '2015-04-11', '2015-04-12', '2015-04-13', '2015-04-14',
       '2015-04-15', '2015-04-16', '2015-04-17', '2015-04-18',
       '2015-04-19', '2015-04-20', '2015-04-21', '2015-04-22',
       '2015-04-23', '2015-04-24', '2015-04-25', '2015-04-26',
       '2015-04-27', '2015-04-28', '2015-04-29', '2015-04-30',
       '2015-05-01', '2015-05-02', '2015-05-03', '2015-05-04',
       '2015-05-05', '2015-05-06', '2015-05-07', '2015-05-08',
       '2015-05-09', '2015-05-10', '2015-05-11', '2015-05-12',
       '2015-05-13', '2015-05-14', '2015-05-15', '2015-05-16',
       '2015-05-17', '2015-05-18', '2015-05-19', '2015-05-20',
       '2015-05-21', '2015-05-22', '2015-05-23', '2015-05-24',
       '2015-05-25', '2015-05-26', '2015-05-27', '2015-05-28',
       '2015-05-29', '2015-05-30', '2015-05-31', '2015-06-01',
       '2015-06-02', '2015-06-03', '2015-06-04', '2015-06-05',
       '2015-06-06', '2015-06-07', '2015-06-08', '2015-06-09',
       '2015-06-10', '2015-06-11', '2015-06-12', '2015-06-13',
       '2015-06-14', '2015-06-15', '2015-06-16', '2015-06-17',
       '2015-06-18', '2015-06-19', '2015-06-20', '2015-06-21',
       '2015-06-22', '2015-06-23', '2015-06-24', '2015-06-25',
       '2015-06-26', '2015-06-27', '2015-06-28', '2015-06-29',
       '2015-06-30', '2015-07-01', '2015-07-02', '2015-07-03',
       '2015-07-04', '2015-07-05', '2015-07-06', '2015-07-07',
       '2015-07-08', '2015-07-09', '2015-07-10', '2015-07-11',
       '2015-07-12', '2015-07-13', '2015-07-14', '2015-07-15',
       '2015-07-16', '2015-07-17', '2015-07-18', '2015-07-19',
       '2015-07-20', '2015-07-21', '2015-07-22', '2015-07-23',
       '2015-07-24', '2015-07-25', '2015-07-26', '2015-07-27',
       '2015-07-28', '2015-07-29', '2015-07-30', '2015-07-31',
       '2015-08-01', '2015-08-02', '2015-08-03', '2015-08-04',
       '2015-08-05', '2015-08-06', '2015-08-07', '2015-08-08',
       '2015-08-09', '2015-08-10', '2015-08-11', '2015-08-12',
       '2015-08-13', '2015-08-14', '2015-08-15', '2015-08-16',
       '2015-08-17', '2015-08-18', '2015-08-19', '2015-08-20',
       '2015-08-21', '2015-08-22', '2015-08-23', '2015-08-24',
       '2015-08-25', '2015-08-26', '2015-08-27', '2015-08-28',
       '2015-08-29', '2015-08-30', '2015-08-31', '2015-09-01',
       '2015-09-02', '2015-09-03', '2015-09-04', '2015-09-05',
       '2015-09-06', '2015-09-07', '2015-09-08', '2015-09-09',
       '2015-09-10', '2015-09-11', '2015-09-12', '2015-09-13',
       '2015-09-14', '2015-09-15', '2015-09-16', '2015-09-17',
       '2015-09-18', '2015-09-19', '2015-09-20', '2015-09-21',
       '2015-09-22', '2015-09-23', '2015-09-24', '2015-09-25',
       '2015-09-26', '2015-09-27', '2015-09-28', '2015-09-29',
       '2015-09-30', '2015-10-01', '2015-10-02', '2015-10-03',
       '2015-10-04', '2015-10-05', '2015-10-06', '2015-10-07',
       '2015-10-08', '2015-10-09', '2015-10-10', '2015-10-11',
       '2015-10-12', '2015-10-13', '2015-10-14', '2015-10-15',
       '2015-10-16', '2015-10-17', '2015-10-18', '2015-10-19',
       '2015-10-20', '2015-10-21', '2015-10-22', '2015-10-23',
       '2015-10-24', '2015-10-25', '2015-10-26', '2015-10-27',
       '2015-10-28', '2015-10-29', '2015-10-30', '2015-10-31',
       '2015-11-01', '2015-11-02', '2015-11-03', '2015-11-04',
       '2015-11-05', '2015-11-06', '2015-11-07', '2015-11-08',
       '2015-11-09', '2015-11-10', '2015-11-11', '2015-11-12',
       '2015-11-13', '2015-11-14', '2015-11-15', '2015-11-16',
       '2015-11-17', '2015-11-18', '2015-11-19', '2015-11-20',
       '2015-11-21', '2015-11-22', '2015-11-23', '2015-11-24',
       '2015-11-25', '2015-11-26', '2015-11-27', '2015-11-28',
       '2015-11-29', '2015-11-30', '2015-12-01', '2015-12-02',
       '2015-12-03', '2015-12-04', '2015-12-05', '2015-12-06',
       '2015-12-07', '2015-12-08', '2015-12-09', '2015-12-10',
       '2015-12-11', '2015-12-12', '2015-12-13', '2015-12-14',
       '2015-12-15', '2015-12-16', '2015-12-17', '2015-12-18',
       '2015-12-19', '2015-12-20', '2015-12-21', '2015-12-22',
       '2015-12-23', '2015-12-24', '2015-12-25', '2015-12-26',
       '2015-12-27', '2015-12-28', '2015-12-29', '2015-12-30', '2015-12-31'], dtype=object)

















In [71]:



    


len(ID)



    


















    
Out[71]:








382

















In [72]:



    


DATA_DC_std_final.shape



    


















    
Out[72]:








(365, 380)

















In [73]:



    


DATA_DC_std_final



    


















    
Out[73]:








array([[  9.18298256e-02,   7.69874827e-02,   7.48233378e-02, ...,
          3.05043804e-01,   1.81773931e-01,   1.35905213e+02],
       [  8.50574659e-02,   7.56067788e-02,   9.60450252e-02, ...,
          1.94220546e+00,   1.40502242e+00,   1.89762477e+02],
       [  6.71859278e-02,   8.57379470e-02,   9.64137381e-02, ...,
          1.45908860e-01,   6.85809862e-01,   2.74516171e+01],
       ..., 
       [  8.71684110e-02,   1.05531781e-01,   1.03264721e-01, ...,
          1.31353913e+00,   4.99144386e+00,   1.23894212e+00],
       [  4.95968497e-02,   1.04620538e-01,   8.48963302e-02, ...,
          1.80628758e+00,   5.63193710e+00,   1.60923984e+00],
       [  6.65027443e-02,   5.06216604e-02,   9.31773175e-02, ...,
          4.81908087e+00,   2.47336636e+00,   2.29587383e+00]])

















In [76]:



    


df_DCstd = pd.DataFrame(data = np.hstack((DATA_DC_std_final, date.reshape([-1,1]))), columns=ID[:-1])
df_DCstd.set_index('date')
df_DC = pd.DataFrame(data = np.hstack((DATA_DC_final, date.reshape([-1,1]))), columns=ID[:-1])
df_DC.set_index('date')



    


















    
Out[76]:










  
    

      
      2134
      3245
      4356
      5467
      6578
      7689
      87910
      981011
      1091112
      11101213
      ...
      36354445
      37364546
      38374647
      39384748
      40394849
      41404950
      42415051
      43425152
      44435253
      45445354
    

    

      date
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    

  
  
    

      2015-01-01
      63.8435
      66.0997
      67.6907
      89.4797
      81.0441
      76.8638
      81.0903
      69.4503
      52.6298
      88.1749
      ...
      110.359
      84.2553
      96.4511
      99.1321
      82.5125
      77.3529
      75.411
      70.7458
      66.1388
      151.8
    

    

      2015-01-02
      64.1266
      66.3452
      67.9904
      89.9214
      81.3556
      76.9514
      81.6516
      69.8965
      53.0818
      88.5745
      ...
      110.511
      83.8233
      96.3742
      99.1411
      82.5272
      77.5084
      77.3286
      72.017
      64.5944
      196.191
    

    

      2015-01-03
      64.3166
      66.5672
      68.2552
      90.2055
      81.6469
      77.0259
      81.9475
      70.4097
      53.8211
      88.8106
      ...
      110.341
      83.6864
      96.2424
      99.0359
      82.4344
      77.3507
      76.9842
      72.1312
      64.6917
      44.894
    

    

      2015-01-04
      38.6869
      40.1053
      41.1478
      54.2852
      49.2244
      46.2452
      49.6201
      42.2292
      31.949
      53.561
      ...
      66.4783
      50.2957
      58.0098
      59.6831
      49.6465
      47.0133
      48.41
      43.7154
      35.1429
      76.8739
    

    

      2015-01-05
      12.9201
      13.4114
      13.7671
      18.1572
      16.4497
      15.4797
      16.6515
      14.0976
      10.6175
      17.9115
      ...
      22.1307
      16.7422
      19.3394
      19.8717
      16.5371
      15.86
      16.3996
      14.2587
      11.8562
      82.6108
    

    

      2015-01-06
      64.7369
      67.1685
      69.5709
      90.8841
      82.2246
      78.0032
      84.0822
      70.3324
      52.3622
      89.8379
      ...
      110.265
      84.5889
      97.2581
      99.5777
      83.0315
      81.6846
      83.4658
      68.4341
      58.0133
      83.7678
    

    

      2015-01-07
      64.6879
      67.2001
      69.7287
      91.091
      80.5328
      80.3128
      84.07
      70.4582
      52.4744
      89.7672
      ...
      109.711
      84.5996
      97.1693
      98.7176
      82.8042
      77.5627
      74.5962
      70.3918
      66.4746
      81.434
    

    

      2015-01-08
      64.7544
      67.2778
      69.9757
      91.4985
      80.6563
      80.751
      84.0332
      70.6868
      52.874
      90.0406
      ...
      109.484
      84.7348
      97.2603
      98.5581
      82.9535
      77.5061
      72.8522
      70.3584
      65.4076
      80.8098
    

    

      2015-01-09
      64.8425
      67.4371
      70.1505
      91.7709
      81.0182
      81.4423
      83.7561
      70.6971
      52.9531
      90.427
      ...
      109.374
      85.1872
      97.3056
      98.6344
      82.9207
      78.1717
      101.677
      85.0221
      60.6745
      68.1954
    

    

      2015-01-10
      65.0032
      67.6553
      70.3889
      92.1649
      82.9333
      79.5121
      83.9696
      70.978
      53.4017
      90.7893
      ...
      109.634
      85.8403
      97.4961
      99.0931
      82.9269
      77.9179
      94.0466
      84.7326
      64.2806
      240.474
    

    

      2015-01-11
      65.1285
      67.8127
      70.4738
      92.4471
      83.8211
      78.3505
      84.3805
      71.002
      53.2683
      91.0886
      ...
      109.832
      86.1021
      97.3717
      99.3295
      82.9049
      78.0745
      92.3736
      83.8458
      64.6419
      400.206
    

    

      2015-01-12
      65.1978
      67.9244
      70.5266
      92.6201
      83.9795
      78.319
      84.6486
      71.1099
      53.2491
      91.263
      ...
      109.871
      85.471
      97.1382
      99.2406
      82.7963
      77.656
      80.5954
      76.9639
      66.6256
      80.782
    

    

      2015-01-13
      65.5597
      68.1364
      70.7198
      92.9368
      84.2801
      78.3576
      85.0926
      71.6283
      53.8277
      91.6569
      ...
      110.721
      85.1634
      97.2501
      99.5664
      82.9682
      77.975
      88.9364
      82.6323
      64.8025
      256.143
    

    

      2015-01-14
      66.0347
      68.201
      71.0369
      92.8713
      84.7627
      77.8831
      85.4771
      71.8277
      54.2533
      91.9712
      ...
      110.856
      85.2969
      97.5221
      99.6585
      83.0327
      78.4381
      94.0812
      86.1293
      64.7595
      86.1258
    

    

      2015-01-15
      66.0422
      68.4587
      71.0062
      93.2097
      84.5544
      78.9377
      86.0543
      71.9125
      54.2122
      92.2648
      ...
      111.166
      84.8558
      97.6584
      99.5393
      83.1209
      78.2888
      86.7395
      81.8434
      66.2151
      81.2831
    

    

      2015-01-16
      66.0978
      68.536
      71.0596
      93.3991
      84.4993
      79.2379
      86.4733
      72.1688
      54.045
      92.4689
      ...
      111.074
      84.8535
      97.6109
      99.3916
      83.0541
      78.8486
      106.611
      90.2709
      60.8124
      81.17
    

    

      2015-01-17
      66.1789
      68.6152
      71.125
      93.5174
      84.5846
      79.3491
      86.6401
      72.4021
      54.2754
      92.6201
      ...
      110.985
      85.2392
      97.5657
      99.3006
      82.9761
      78.131
      82.5667
      78.9442
      66.534
      76.7331
    

    

      2015-01-18
      66.2807
      68.7939
      71.3338
      93.8778
      84.8447
      79.4951
      86.8503
      72.886
      54.8725
      92.916
      ...
      110.664
      85.3161
      97.5108
      99.1219
      82.8658
      78.239
      98.1446
      86.9656
      61.7902
      81.0359
    

    

      2015-01-19
      66.4084
      68.9865
      71.5737
      93.9862
      85.1684
      79.5663
      87.3724
      72.9841
      54.6623
      93.2836
      ...
      110.968
      85.5434
      97.8999
      99.2768
      83.0598
      78.8565
      102.853
      91.7943
      63.0376
      81.7021
    

    

      2015-01-20
      66.4362
      69.0789
      71.6424
      94.1959
      85.2952
      79.6394
      87.527
      73.1589
      54.7419
      93.4146
      ...
      110.626
      85.6373
      97.7772
      99.0495
      82.9377
      78.571
      95.9348
      88.9963
      63.5811
      81.481
    

    

      2015-01-21
      66.5728
      69.2777
      71.8569
      94.4128
      85.4672
      80.0305
      87.8714
      73.4379
      54.8452
      93.7026
      ...
      110.936
      85.8918
      98.0435
      99.2034
      83.0643
      78.7536
      101.163
      90.9031
      61.2592
      81.6693
    

    

      2015-01-22
      66.6586
      69.3919
      71.9935
      94.4834
      85.5374
      80.4801
      88.223
      73.4181
      54.5172
      93.9231
      ...
      110.304
      86.5263
      98.1731
      99.1569
      82.9201
      83.8498
      127.156
      108.216
      58.2112
      82.8648
    

    

      2015-01-23
      66.8745
      69.4323
      72.0034
      94.7379
      85.4705
      80.7883
      88.4101
      73.4011
      54.3112
      94.1111
      ...
      109.49
      86.783
      98.4478
      98.9568
      83.0485
      81.4606
      121.738
      98.1922
      53.3672
      82.9331
    

    

      2015-01-24
      67.0606
      69.5765
      72.1514
      94.9547
      85.5798
      81.1007
      88.6735
      73.6179
      54.447
      94.3798
      ...
      109.634
      87.2337
      98.7685
      98.8521
      83.5083
      78.8757
      104.713
      92.6442
      59.807
      82.9427
    

    

      2015-01-25
      67.0912
      69.642
      72.2338
      95.1243
      85.519
      81.4296
      88.8313
      73.8073
      54.5445
      94.5164
      ...
      109.614
      87.5091
      98.7329
      98.7707
      83.5733
      80.5123
      118.453
      97.7392
      53.5346
      83.2605
    

    

      2015-01-26
      67.0714
      69.6887
      72.289
      95.03
      85.6185
      81.546
      89.0717
      73.6462
      54.036
      94.5305
      ...
      109.91
      87.3338
      98.7509
      98.8629
      83.7169
      87.0499
      121.817
      108.291
      55.835
      82.6606
    

    

      2015-01-27
      67.0271
      69.6962
      72.3493
      95.1431
      85.3885
      81.9645
      88.9897
      73.9195
      54.5073
      94.6813
      ...
      109.71
      87.5486
      98.4908
      98.7204
      83.64
      78.2012
      83.3143
      82.189
      66.4537
      82.7567
    

    

      2015-01-28
      66.9051
      69.8216
      72.4026
      95.4682
      85.5615
      81.9065
      88.9303
      74.1626
      54.8862
      94.7708
      ...
      109.441
      87.5351
      98.2579
      98.5321
      83.4517
      77.8579
      82.7273
      80.9534
      66.3598
      82.2862
    

    

      2015-01-29
      67.0931
      69.9856
      72.6038
      95.8029
      85.9521
      82.0559
      89.1452
      74.582
      55.2848
      95.162
      ...
      109.347
      88.2951
      98.5745
      98.8312
      83.7101
      78.0145
      85.1193
      83.4296
      66.292
      82.3122
    

    

      2015-01-30
      67.2265
      70.0534
      72.7259
      95.9301
      86.2645
      81.8589
      89.3563
      74.7503
      55.5082
      95.3222
      ...
      109.303
      88.4042
      98.5887
      99.0366
      83.4031
      77.9823
      84.2015
      82.1358
      66.4374
      82.2636
    

    

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      2015-12-02
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      2015-12-07
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      2015-12-08
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      2015-12-11
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      2015-12-18
      60.4948
      64.0526
      66.0747
      87.0553
      77.5951
      77.294
      80.0428
      67.2934
      50.3255
      83.6826
      ...
      89.2559
      77.2279
      104.1
      102.569
      84.4492
      81.3283
      75.6412
      83.1061
      72.4988
      97.2807
    

    

      2015-12-19
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      2015-12-20
      60.7762
      64.2869
      66.2369
      87.3776
      77.6984
      77.5245
      80.1479
      66.6817
      49.6041
      83.9267
      ...
      76.7287
      66.5889
      104.695
      104.825
      84.5448
      82.893
      74.7189
      85.6549
      71.1145
      101.232
    

    

      2015-12-21
      60.9198
      64.4514
      66.251
      87.7588
      77.5358
      79.4867
      80.6228
      65.7685
      48.8547
      84.1981
      ...
      84.0896
      73.1135
      105.249
      106.113
      84.5578
      82.2235
      75.3681
      86.6139
      71.4747
      100.269
    

    

      2015-12-22
      60.9821
      64.5592
      66.064
      88.6287
      78.3227
      78.3736
      79.9984
      66.0705
      49.8457
      84.307
      ...
      85.1527
      74.2462
      104.785
      108.688
      84.1037
      82.2443
      73.0869
      91.0303
      71.7693
      101.047
    

    

      2015-12-23
      61.1329
      65.6483
      64.8872
      88.5553
      79.4796
      76.8742
      80.1775
      66.4781
      50.203
      84.3372
      ...
      79.102
      69.984
      105.035
      110.761
      84.1247
      82.6329
      72.2455
      93.9754
      69.4701
      102.733
    

    

      2015-12-24
      61.3869
      65.9965
      64.2426
      88.453
      79.556
      76.4227
      80.7595
      67.0554
      50.6257
      84.4625
      ...
      91.7657
      78.9481
      104.77
      106.783
      84.2643
      81.8898
      74.8732
      90.246
      70.1662
      98.9394
    

    

      2015-12-25
      61.7064
      66.1242
      64.1761
      88.5892
      79.5884
      76.5556
      81.2072
      67.4102
      51.0682
      84.7919
      ...
      108.119
      90.9172
      104.469
      102.326
      84.3311
      80.7244
      77.5977
      79.9972
      67.9625
      95.3292
    

    

      2015-12-26
      62.0499
      66.2699
      64.17
      88.8987
      79.5409
      76.6051
      81.8735
      67.6459
      51.3019
      85.0445
      ...
      109.407
      92.8032
      104.74
      105.005
      84.1778
      81.1575
      77.3467
      82.5786
      73.0625
      94.3514
    

    

      2015-12-27
      62.253
      66.2892
      64.3528
      89.2046
      79.4985
      76.8444
      82.2759
      67.9649
      51.6012
      85.2876
      ...
      111.483
      92.4842
      104.261
      101.721
      84.102
      80.6633
      77.8721
      78.8345
      67.3613
      94.2932
    

    

      2015-12-28
      62.4231
      66.3721
      64.4575
      89.827
      79.6304
      77.0146
      82.8089
      68.5421
      52.2542
      85.5874
      ...
      111.701
      92.9049
      104.288
      102.916
      83.8979
      80.5931
      77.6967
      79.9056
      69.5441
      93.2352
    

    

      2015-12-29
      62.6342
      66.5328
      64.7304
      90.3115
      79.7114
      77.4118
      83.3768
      68.9587
      52.6016
      85.8828
      ...
      113.385
      93.6185
      104.674
      103.904
      83.9856
      80.9981
      77.435
      81.5359
      74.5301
      92.9706
    

    

      2015-12-30
      62.8689
      66.8061
      64.834
      90.7823
      79.8114
      77.7134
      84.0817
      69.2651
      52.6426
      86.2174
      ...
      112.701
      91.2486
      105.001
      105.382
      84.2332
      81.5697
      76.8694
      82.763
      77.7329
      93.169
    

    

      2015-12-31
      63.0697
      66.9187
      65.0164
      90.9383
      79.9296
      77.8161
      84.5502
      69.3432
      52.34
      86.3772
      ...
      82.6317
      64.6329
      104.808
      109.338
      83.9499
      84.2479
      77.0956
      84.9949
      71.5539
      97.5374
    

  



365 rows × 380 columns



















In [77]:



    


df.to_csv("../data/ChungCheonDC/CompositeETCdata.csv")
df_DC.to_csv("../data/ChungCheonDC/CompositeDCdata.csv")
df_DCstd.to_csv("../data/ChungCheonDC/CompositeDCstddata.csv")

Content source: sgkang/DamGeophysics

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