01: remove outliers from data
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@ -20,10 +20,9 @@ import seaborn as sns
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# %% Data
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# %% Data
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data = pd.read_csv("../data/melb_data.csv").dropna()
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data = pd.read_csv("../data/melb_data.csv").dropna()
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# Ein Outlier, blöder Arsch
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data = data[(data["BuildingArea"] < 1000) ]
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# TODO: remove outlier from actual data, not just diagram
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ax = sns.scatterplot(x=data['BuildingArea'], y=data['Price'])
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ax = sns.scatterplot(x=data['BuildingArea'], y=data['Price'])
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ax.set(xlim=(0, 1000))
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# ax.set(xlim=(0, 1000)) # brauch ich nicht mehr wenn ich die outlier aus den daten rausschmeiße
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# %% linear regression
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# %% linear regression
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