Ren data
Analysera IoT-data i Python
Matthias Voppichler
IT Developer
Saknad data
Orsaker till saknad data från IoT-enheter
- Instabil nätverksanslutning
- Strömavbrott
- Andra externa faktorer
När man hanterar datakvalitet
- Under datainsamling
- Under analys
Hantera saknad data
Metoder för att hantera saknad data
- fylla
- medelvärde
- median
- framåtfyllning
- bakåtfyllning
- ta bort
- avbryt analysen
Identifiera saknade värden
df.info()
<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 12 entries, 2018-10-15 08:00:00 to 2018-10-15 08:55:00
Data columns (total 3 columns):
temperature 8 non-null float64
humidity 8 non-null float64
precipitation 12 non-null float64
dtypes: float64(3)
memory usage: 384.0 bytes
Ta bort saknade värden
print(df.head())
temperature humidity precipitation
timestamp
2018-10-15 08:00:00 16.7 64.2 0.0
2018-10-15 08:05:00 16.6 NaN 0.0
2018-10-15 08:10:00 16.5 65.3 0.0
2018-10-15 08:15:00 NaN 65.0 0.0
2018-10-15 08:20:00 16.8 64.3 0.0
df.dropna()
temperature humidity precipitation
timestamp
2018-10-15 08:00:00 16.7 64.2 0.0
2018-10-15 08:10:00 16.5 65.3 0.0
2018-10-15 08:20:00 16.8 64.3 0.0
Fylla saknade värden
df
temperature humidity precipitation
timestamp
2018-10-15 08:00:00 16.7 64.2 0.0
2018-10-15 08:05:00 16.6 NaN 0.0
2018-10-15 08:10:00 17.0 65.3 0.0
2018-10-15 08:15:00 NaN 65.0 0.0
2018-10-15 08:20:00 16.8 64.3 0.0
df.fillna(method="ffill")
temperature humidity precipitation
timestamp
2018-10-15 08:00:00 16.7 64.2 0.0
2018-10-15 08:05:00 16.6 64.2 0.0
2018-10-15 08:10:00 17.0 65.3 0.0
2018-10-15 08:15:00 17.0 65.0 0.0
2018-10-15 08:20:00 16.8 64.3 0.0
Avbruten mätning
print(df.head())
timestamp temperature humidity
2018-10-15 00:00:00 13.5 84.7
2018-10-15 00:10:00 13.3 85.6
2018-10-15 00:20:00 12.9 88.8
2018-10-15 00:30:00 12.8 89.2
2018-10-15 00:40:00 13.0 87.7
print(df.isna().sum())
temperature 0
humidity 0
dtype: int64
df_res = df.resample("10min").last()
print(df_res.head())
timestamp temperature humidity
2018-10-15 00:00:00 13.5 84.7
2018-10-15 00:10:00 13.3 85.6
2018-10-15 00:20:00 12.9 88.8
2018-10-15 00:30:00 12.8 89.2
2018-10-15 00:40:00 13.0 87.7
print(df_res.isna().sum())
temperature 34
humidity 34
dtype: int64
Avbruten mätning
df_res.plot(title="Environment")
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Analysera IoT-data i Python
