Imputasi data deret waktu

Menangani Data Hilang di Python

Suraj Donthi

Deep Learning & Computer Vision Consultant

Dataset Airquality

import pandas as pd
airquality = pd.read_csv('air-quality.csv', parse_dates='Date', 
                                index_col='Date')

airquality.head()

             Ozone    Solar    Wind    Temp
Date                
1976-05-01    41.0    190.0     7.4    67
1976-05-02    36.0    118.0     8.0    72
1976-05-03    12.0    149.0    12.6    74
1976-05-04    18.0    313.0    11.5    62
1976-05-05     NaN      NaN    14.3    56

Dataset Airquality

airquality.isnull().sum()

Ozone    37
Solar     7
Wind      0
Temp      0
dtype: int64

airquality.isnull.mean() * 100

Ozone    24.183007
Solar     4.575163
Wind      0.000000
Temp      0.000000
dtype: float64

.fillna() method

Atribut method di .fillna() dapat diatur ke

'ffill' atau 'pad'
'bfill' atau 'backwardfill'

Metode ffill

Ganti NaN dengan nilai terakhir yang teramati
pad sama dengan 'ffill'

airquality.fillna(method='ffill', inplace=True)



airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01     NaN
1976-06-02     NaN
1976-06-03     NaN
1976-06-04     NaN
1976-06-05     NaN
1976-06-06     NaN
1976-06-07    29.0
1976-06-08     NaN
1976-06-09    71.0

airquality.fillna(method='ffill', 
                         inplace=True)
airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01    37.0
1976-06-02    37.0
1976-06-03    37.0
1976-06-04    37.0
1976-06-05    37.0
1976-06-06    37.0
1976-06-07    29.0
1976-06-08    29.0
1976-06-09    71.0

Metode bfill

Ganti NaN dengan nilai teramati berikutnya
backfill sama dengan 'bfill'

df.fillna(method='bfill', inplace=True)



airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01     NaN
1976-06-02     NaN
1976-06-03     NaN
1976-06-04     NaN
1976-06-05     NaN
1976-06-06     NaN
1976-06-07    29.0
1976-06-08     NaN
1976-06-09    71.0

airquality.fillna(method='bfill', 
                         inplace=True)
airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01    29.0
1976-06-02    29.0
1976-06-03    29.0
1976-06-04    29.0
1976-06-05    29.0
1976-06-06    29.0
1976-06-07    29.0
1976-06-08    71.0
1976-06-09    71.0

Metode .interpolate()

Metode .interpolate() memperluas deret nilai ke nilai yang hilang

Atribut method di .interpolate() dapat diatur ke

'linear'
'quadratic'
'nearest'

Interpolasi linear

Imputasi linear atau dengan jarak sama

df.interpolate(method='linear', inplace=True)

cuplikan interpolasi linear



airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01     NaN
1976-06-02     NaN
1976-06-03     NaN
1976-06-04     NaN
1976-06-05     NaN
1976-06-06     NaN
1976-06-07    29.0
1976-06-08     NaN
1976-06-09    71.0

airquality.interpolate(
          method='linear', inplace=True)
airquality['Ozone'][30:40]

Date         Ozone        
1976-05-31    37.0
1976-06-01    35.9
1976-06-02    34.7
1976-06-03    33.6
1976-06-04    32.4
1976-06-05    31.3
1976-06-06    30.1
1976-06-07    29.0
1976-06-08    50.0
1976-06-09    71.0

Interpolasi kuadratik

Imputasi kuadratik

df.interpolate(method='quadratic', inplace=True)

cuplikan interpolasi kuadratik



airquality['Ozone'][30:39]

             Ozone
Date                
1976-05-31    37.0
1976-06-01     NaN
1976-06-02     NaN
1976-06-03     NaN
1976-06-04     NaN
1976-06-05     NaN
1976-06-06     NaN
1976-06-07    29.0
1976-06-08     NaN

airquality.interpolate(
  method='quadratic', inplace=True)
airquality['Ozone'][30:39]

             Ozone
Date                
1976-05-31    37.0
1976-06-01   -38.4
1976-06-02   -79.4
1976-06-03   -85.9
1976-06-04   -62.4
1976-06-06    -2.8
1976-06-07    29.0
1976-06-08    62.2

Imputasi nilai terdekat

Imputasi dengan nilai terdekat yang teramati

df.interpolate(method='nearest', inplace=True)

cuplikan interpolasi nilai terdekat



airquality['Ozone'][30:39]

Date         Ozone        
1976-05-31    37.0
1976-06-01     NaN
1976-06-02     NaN
1976-06-03     NaN
1976-06-04     NaN
1976-06-05     NaN
1976-06-06     NaN
1976-06-07    29.0
1976-06-08     NaN

airquality.interpolate(
  method='nearest', inplace=True)
airquality['Ozone'][30:39]

Date         Ozone        
1976-05-31    37.0
1976-06-01    37.0
1976-06-02    37.0
1976-06-03    37.0
1976-06-04    29.0
1976-06-05    29.0
1976-06-06    29.0
1976-06-07    29.0
1976-06-08    29.0

Ayo berlatih!

Menangani Data Hilang di Python