如何检查DataFrame是否为空？

Question

我想检查DataFrame是否为空:

    BTC_ewma_24  ETH_ewma_24  DASH_ewma_24
24  4011.235578   334.597119        281.15
25  4011.285662   334.591056        281.15
26  4011.373673   334.603479        281.15
27  4011.453068   334.614686        281.15
28  4011.526571   334.624813        281.15
29  4011.591356   334.633980        281.15
30  4011.650075   334.642288        281.15
31  4011.703366   334.649828        281.15

我试过if(self.mean_exp.bool() == False): 但它回答了我:

ValueError: The truth value of a DataFrame is ambiguous.
Use a.empty, a.bool(), a.item(), a.any() or a.all().

好像它甚至没有注意到我使用过 .bool()

然后我用a.empty它并且它回答了我:

AttributeError: 'list' object has no attribute 'empty'

Answer 1

IIUC:有.empty属性:

数据帧:

In [86]: pd.DataFrame().empty
Out[86]: True

In [87]: pd.DataFrame([1,2,3]).empty
Out[87]: False

系列:

In [88]: pd.Series().empty
Out[88]: True

In [89]: pd.Series([1,2,3]).empty
Out[89]: False

注意:len(df)与df.empty方法相比,检查DF()的长度可能会节省几毫秒;-)

In [142]: df = pd.DataFrame()

In [143]: %timeit df.empty
8.25 µs ± 22.4 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

In [144]: %timeit len(df)
2.35 µs ± 7.56 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

In [145]: df = pd.DataFrame(np.random.randn(10*5, 3), columns=['a', 'b', 'c'])

In [146]: %timeit df.empty
15.3 µs ± 269 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

In [147]: %timeit len(df)
3.58 µs ± 12.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)