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95 lines
2.6 KiB
Python
95 lines
2.6 KiB
Python
# coding=utf-8
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#-----------------------------------------------------
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# Author: Yaqiang Wang
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# Date: 2018-8-29
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# Purpose: MeteoInfo groupby module
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# Note: Jython
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#-----------------------------------------------------
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from org.meteoinfo.data.dataframe import DataFrame as MIDataFrame
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from org.meteoinfo.data.dataframe import Series as MISeries
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import dataframe
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import series
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class GroupBy(object):
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def __init__(self, groupby):
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'''
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GroupBy
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:param groupby: MIGroupBy object
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'''
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self._groupby = groupby
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def count(self):
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'''
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Compute count of groups.
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'''
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r = self._groupby.count()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def sum(self):
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'''
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Compute sum of groups.
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'''
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r = self._groupby.sum()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def mean(self):
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'''
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Compute mean of groups.
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'''
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r = self._groupby.mean()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def max(self):
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'''
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Compute maximum of groups.
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'''
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r = self._groupby.max()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def min(self):
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'''
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Compute minimum of groups.
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'''
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r = self._groupby.min()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def median(self):
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'''
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Compute median of groups.
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'''
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r = self._groupby.median()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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def std(self):
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'''
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Compute standard deviation of groups.
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'''
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r = self._groupby.median()
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if isinstance(r, MIDataFrame):
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return dataframe.DataFrame(dataframe=r)
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else:
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return series.Series(series=r)
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######################################################## |