具有多级列的 Pandas Groupby

Question

我想知道如何改造表格并获得我想要的结果：

我的示例数据集：

df=pd.DataFrame({

    "ID":[111,111,111,111,222,222,222,333,333],

    "Section":["CS01","CS01","IT01","IT01","CS02","CS02","CS02","HS01","HS01"],

    "Subject":["Hist","Pol","Pol","Arts","Pol","Hist","Arts","Pol","Hist"],

    "Activity":["Quiz 1","Quiz 2","Quiz 3","Quiz 1","Quiz 2","Quiz 3","Quiz 1","Quiz 2","Quiz 3"],

    "Pass":[1,0,0,1,1,1,0,1,0],

    })

它看起来像什么：

    ID      Section     Subject     Activity    Pass

0   111     CS01        Hist        Quiz 1      1

1   111     CS01        Pol         Quiz 2      0

2   111     IT01        Pol         Quiz 3      0

3   111     IT01        Arts        Quiz 1      1

4   222     CS02        Pol         Quiz 2      1

5   222     CS02        Hist        Quiz 3      1

6   222     CS02        Arts        Quiz 1      0

7   333     HS01        Pol         Quiz 2      1

8   333     HS01        Hist        Quiz 3      0

我正在尝试做的事情：

ID  Section Subject Quiz 1      Quiz 2      Quiz 3      

                    0   1   NA  0   1   NA  0   1   NA

111 CS01    Hist    0   1   0   0   0   1   0   0   1

111 CS01    Pol     0   0   1   1   0   0   0   0   1

111 IT01    Arts    0   1   0   0   0   1   0   0   1

111 IT01    Pol     0   0   1   0   0   1   1   0   0

222 CS02    Arts    1   0   0   0   0   0   0   0   0

222 CS02    Hist    0   0   1   0   0   1   0   1   0

222 CS02    Pol     0   0   1   0   1   0   0   0   1

333 HS01    Hist    0   0   1   0   0   1   1   0   0

333 HS01    Pol     0   0   1   0   1   0   0   0   1

我想要的是将“主题”列设置为级别 2，将“通过”列设置为级别 1，并使用“NA”列。

到目前为止我只有这个：

df.groupby(["ID","Section", "Subject","Activity"])["Pass"].value_counts().unstack().fillna(0)

但这没有“NA”列，也没有级别 2 的“活动”

Answer 1

想法是在第一步中创建所有可能的组合，Series.reindex然后在 value_counts中MultiIndex.from_product应用您的解决方案：MultiIndexdropna=Falses = df.set_index(["ID","Section", "Subject","Activity"])["Pass"]&nbsp;df = (s.reindex(pd.MultiIndex.from_product(s.index.levels))&nbsp; &nbsp; &nbsp; &nbsp;.groupby(level=[0,1,2,3])&nbsp; &nbsp; &nbsp; &nbsp;.value_counts(dropna=False)&nbsp; &nbsp; &nbsp; &nbsp;.unstack([3,4], fill_value=0)&nbsp; &nbsp; &nbsp; &nbsp;.sort_index(axis=1))print (df)Activity&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Quiz 1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Pass&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0.0 1.0 NaN&nbsp; &nbsp; 0.0 1.0 NaN&nbsp; &nbsp; 0.0 1.0 NaNID&nbsp; Section Subject&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;111 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 1&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 1&nbsp; &nbsp;0&nbsp; &nbsp;0222 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1333 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 1&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;编辑：处理重复项的解决方案：df=pd.DataFrame({&nbsp; &nbsp; "ID":[111,111,111,111,222,222,222,333,333],&nbsp; &nbsp; "Section":["CS01","CS01","IT01","IT01","CS02","CS02","CS02","HS01","HS01"],&nbsp; &nbsp; "Subject":["Hist","Pol","Pol","Arts","Pol","Hist","Arts","Pol","Hist"],&nbsp; &nbsp; "Activity":["Quiz 1","Quiz 2","Quiz 3","Quiz 1","Quiz 2","Quiz 3","Quiz 1","Quiz 2","Quiz 3"],&nbsp; &nbsp; "Pass":[1,0,0,1,1,1,0,1,0],&nbsp; &nbsp; })df = pd.concat([df, df.head()])print (df)&nbsp; &nbsp; ID Section Subject Activity&nbsp; Pass0&nbsp; 111&nbsp; &nbsp; CS01&nbsp; &nbsp; Hist&nbsp; &nbsp;Quiz 1&nbsp; &nbsp; &nbsp;11&nbsp; 111&nbsp; &nbsp; CS01&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp;02&nbsp; 111&nbsp; &nbsp; IT01&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp;03&nbsp; 111&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp;Quiz 1&nbsp; &nbsp; &nbsp;14&nbsp; 222&nbsp; &nbsp; CS02&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp;15&nbsp; 222&nbsp; &nbsp; CS02&nbsp; &nbsp; Hist&nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp;16&nbsp; 222&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp;Quiz 1&nbsp; &nbsp; &nbsp;07&nbsp; 333&nbsp; &nbsp; HS01&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp;18&nbsp; 333&nbsp; &nbsp; HS01&nbsp; &nbsp; Hist&nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp;00&nbsp; 111&nbsp; &nbsp; CS01&nbsp; &nbsp; Hist&nbsp; &nbsp;Quiz 1&nbsp; &nbsp; &nbsp;1 <- duplicates1&nbsp; 111&nbsp; &nbsp; CS01&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp;0 <- duplicates2&nbsp; 111&nbsp; &nbsp; IT01&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp;0 <- duplicates3&nbsp; 111&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp;Quiz 1&nbsp; &nbsp; &nbsp;1 <- duplicates4&nbsp; 222&nbsp; &nbsp; CS02&nbsp; &nbsp; &nbsp;Pol&nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp;1 <- duplicates首先使用SeriesGroupBy.value_counts并重塑最后一个级别 by ，添加bySeries.unstack的所有可能组合，如果所有值都在由和测试的两列中，则添加由 填充的列，最后for在列中，更改级别的顺序并排序：levelsDataFrame.reindexNaN10DataFrame.eqDataFrame.allunstackMultiIndexMultiIndexdf1 = (df.groupby(["ID","Section", "Subject","Activity"])["Pass"]&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;.value_counts()&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;.unstack(fill_value=0))df1 = df1.reindex(pd.MultiIndex.from_product(df1.index.levels), fill_value=0)df1[np.nan] = df1.eq(0).all(axis=1).view('i1')df1 = df1.unstack().swaplevel(1,0, axis=1).sort_index(axis=1)print (df1)Activity&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Quiz 1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Quiz 2&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Quiz 3&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Pass&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0.0 1.0 NaN&nbsp; &nbsp; 0.0 1.0 NaN&nbsp; &nbsp; 0.0 1.0 NaNID&nbsp; Section Subject&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;111 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;2&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 2&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;2&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 2&nbsp; &nbsp;0&nbsp; &nbsp;0222 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;2&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1333 CS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; CS02&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; HS01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 1&nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;1&nbsp; &nbsp;0&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; IT01&nbsp; &nbsp; Arts&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Hist&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Pol&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1&nbsp; &nbsp; &nbsp; 0&nbsp; &nbsp;0&nbsp; &nbsp;1