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@ -72,7 +72,7 @@ lat = -33.75
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lon = 151.25
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lon = 151.25
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# Create temporary dataframe at specific location
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# Create temporary dataframe at specific location
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df1 = df.loc[lat, lon]
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df1 = df.loc[(lat, lon), :]
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# Plot time series
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# Plot time series
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fig, ax = plt.subplots(1, 1, figsize=(6, 4))
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fig, ax = plt.subplots(1, 1, figsize=(6, 4))
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@ -112,14 +112,11 @@ dates = df.index.get_level_values('time').unique()
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fig, ax = plt.subplots(3, 4)
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fig, ax = plt.subplots(3, 4)
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for i, date in enumerate(dates):
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for i, date in enumerate(dates):
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# Get temporary dataframe with only one date
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# Get temporary dataframe with only one date ('slice(None)' is ':')
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df1 = df[df.index.get_level_values('time') == date]
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df1 = df.loc[(slice(None), slice(None), date), :]
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# Remove date from multi-index
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df1.index = df1.index.droplevel(-1)
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# Split multi-index so that rows=latitude and columns=longitude
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# Split multi-index so that rows=latitude and columns=longitude
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grid = df1.unstack()
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grid = df1.unstack().unstack()
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# Plot colour map for current month
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# Plot colour map for current month
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a = ax.ravel()[i]
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a = ax.ravel()[i]
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