获取pandas datafram中最大连续空行数

Question

我有一个数据帧，我需要从开始日期和结束日期获取较大的空行序列，以便进一步研究。我的索引是DatatimeIndex对象，DataFrame如下所示：

                           C Instalation  N Serial Number D Register Read  \
Z Ts Read                                                                    
2016-12-25 00:00:00  PT0002000080299561BD   10101516046456              A+   
2016-12-25 00:15:00  PT0002000080299561BD   10101516046456              A+   
2016-12-25 00:30:00  PT0002000080299561BD   10101516046456              A+   
2016-12-25 00:45:00  PT0002000080299561BD   10101516046456              A+   
2016-12-25 01:00:00  PT0002000080299561BD   10101516046456              A+   

                    M Read D Read Unit  
Z Ts Read                               
2016-12-25 00:00:00  0,002         kWh  
2016-12-25 00:15:00  0,002         kWh  
2016-12-25 00:30:00  0,002         kWh  
2016-12-25 00:45:00  0,002         kWh  
2016-12-25 01:00:00  0,002         kWh 

NaN值可以分散在列数据帧中，没有问题。但我不介意它们是连续的。在这种情况下，我想知道每一行至少有一个NaN值，起始值和结束值index，并计算两者之间的范围差。最后我想得到更大的射程。在

有可能这样做吗？在

Answer 1

我不确定我100%理解Q，但也许这就是你想要的：

df = pd.DataFrame({"a": [1, 2, 3, np.nan, np.nan, np.nan, 7, 8], "b": [1, 2, 3, np.nan, 5, 6, 7, 8]}

print df

     a    b
0  1.0  1.0
1  2.0  2.0
2  3.0  3.0
3  NaN  NaN
4  NaN  5.0
5  NaN  6.0
6  7.0  7.0
7  8.0  8.0

counts = df.isnull()
counts[~counts] = np.nan
print counts

    a    b
0  NaN  NaN
1  NaN  NaN
2  NaN  NaN
3  1.0  1.0
4  1.0  NaN
5  1.0  NaN
6  NaN  NaN
7  NaN  NaN

runs = counts.cumsum()
print runs

     a    b
0  NaN  NaN
1  NaN  NaN
2  NaN  NaN
3  1.0  1.0
4  2.0  NaN
5  3.0  NaN
6  NaN  NaN
7  NaN  NaN

runs.max(axis=0)

a    3.0
b    1.0
dtype: float64