python - Pandas ，值错误

Question

我的 Excel 中有以下数据:

SCENARIO    DATE    POD         AREA    IDOC    STATUS  TYPE
AAA   02.06.2015    JKJKJKJKJKK 4210    713375  51         1
AAA   02.06.2015    JWERWERE    4210    713375  51         1
AAA   02.06.2015    JAFDFDFDFD  4210    713375  51         9
BBB   02.06.2015    AAAAAAAA    5400    713504  51        43
CCC   05.06.2015    BBBBBBBBBB  4100    756443  51       187
AAA   05.06.2015    EEEEEEEE    4100    756457  53       228

我想实现以下目标:

SCENARIO   STATUS   TYPE  COUNT(TYPE)
AAA        51       1     2
                    9     1
           53       228   1
BBB        51       43    1
CCC        51       187   1

我尝试了以下方法，但它对每一列进行聚合，而且类型显示为浮点，即:

SCENARIO STATUS TYPE
E01      51     1.0     23   23   23   23       23       23   23   23     2
                4.0     89   89   89   89       89       89   89   89     8
                13.0    21   21   21   21       21       21   21   21     2
                20.0    57   57   57   57       57       57   57   57     5
                29.0     5    5    5    5        5        5    5    5

我希望这里只显示一个“计数”，一列。 这是我尝试过的代码:

xl = pd.ExcelFile("MRD.xlsx")
df = xl.parse("Sheet3") 
print (df.column.values)

# The following gave ValueError: Cannot label index with a null key
# dfi = df.pivot('SCENARIO)

# Here i do not actually need it to count every column, just a specific one
table = df.groupby(["SCENARIO", "STATUS", "TYPE"]).agg(['count']
writer = pd.ExcelWriter('pandas.out.xlsx', engine='xlsxwriter')
table.to_excel(writer, sheet_name='Sheet1')
writer.save()

提前致谢!

Answer 1

使用GroupBy.count如果不需要需要计数NaNs，则在[]中指定列:

table = df.groupby(["SCENARIO", "STATUS", "TYPE"])['TYPE'].count()
print (table)
SCENARIO  STATUS  TYPE
AAA       51      1       2
                  9       1
          53      228     1
BBB       51      43      1
CCC       51      187     1
Name: TYPE, dtype: int64

或者使用GroupBy.size ，列指定不是必需的，但区别在于它还计数 NaN:

table = df.groupby(["SCENARIO", "STATUS", "TYPE"]).size()
print (table)
SCENARIO  STATUS  TYPE
AAA       51      1       2
                  9       1
          53      228     1
BBB       51      43      1
CCC       51      187     1
dtype: int64

如果需要来自MultiIndex Series的列:

table = (df.groupby(["SCENARIO", "STATUS", "TYPE"])['TYPE']
           .count()
           .reset_index(name='COUNT(TYPE)'))
print (table)
  SCENARIO  STATUS  TYPE  COUNT(TYPE)
0      AAA      51     1            2
1      AAA      51     9            1
2      AAA      53   228            1
3      BBB      51    43            1
4      CCC      51   187            1

table = (df.groupby(["SCENARIO", "STATUS", "TYPE"])
           .size()
           .reset_index(name='COUNT(TYPE)') )

print (table)
  SCENARIO  STATUS  TYPE  COUNT(TYPE)
0      AAA      51     1            2
1      AAA      51     9            1
2      AAA      53   228            1
3      BBB      51    43            1
4      CCC      51   187            1

最后，如果不需要将名为索引的第一列写入excel:

table.to_excel(writer, sheet_name='Sheet1', index=False)