测试是否存在Pandas DataFrame [英] Testing if a pandas DataFrame exists
问题描述
在我的代码中，我有几个变量，这些变量可以包含pandas DataFrame或根本不包含任何变量.假设我要测试并查看是否已创建某个DataFrame.我的第一个想法就是要像这样测试它:
In my code, I have several variables which can either contain a pandas DataFrame or nothing at all. Let's say I want to test and see if a certain DataFrame has been created yet or not. My first thought would be to test for it like this:
if df1:
# do something
但是，该代码会以这种方式失败:
However, that code fails in this way:
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
足够公平.理想情况下，我希望有一个适用于DataFrame或Python None的状态测试.
Fair enough. Ideally, I would like to have a presence test that works for either a DataFrame or Python None.
这是一种可行的方法:
if not isinstance(df1, type(None)):
# do something
但是，类型测试真的很慢.
However, testing for type is really slow.
t = timeit.Timer('if None: pass')
t.timeit()
# approximately 0.04
t = timeit.Timer('if isinstance(x, type(None)): pass', setup='x=None')
t.timeit()
# approximately 0.4
太好了.除了缓慢之外，对NoneType的测试也不是很灵活.
Ouch. Along with being slow, testing for NoneType isn't very flexible, either.
一种不同的解决方案是将df1初始化为一个空的DataFrame，以便在null和非null情况下类型都相同.然后，我可以使用len()或any()或类似的东西进行测试.但是，制作一个空的DataFrame似乎是一种愚蠢且浪费的事情.
A different solution would be to initialize df1 as an empty DataFrame, so that the type would be the same in both the null and non-null cases. I could then just test using len(), or any(), or something like that. Making an empty DataFrame seems kind of silly and wasteful, though.
另一种解决方案是使用一个指示符变量:df1_exists，在创建df1之前将其设置为False.然后，我将测试df1_exists，而不是测试df1.但这似乎也不是那么优雅.
Another solution would be to have an indicator variable: df1_exists, which is set to False until df1 is created. Then, instead of testing df1, I would be testing df1_exists. But this doesn't seem all that elegant, either.
是否有更好，更Pythonic的方式来解决此问题?我是否想念某些东西，或者这仅仅是大熊猫所有令人敬畏的事情的尴尬副作用?
Is there a better, more Pythonic way of handling this issue? Am I missing something, or is this just an awkward side effect all the awesome things about pandas?
推荐答案
选项1 (我的首选选项)
Option 1 (my preferred option)
如果您喜欢这种方法，请选择他的答案
Please select his answer if you like this approach
使用None初始化变量，然后在使用None进行操作之前先检查None是非常习惯的python.
It is very idiomatic python to initialize a variable with None then check for None prior to doing something with that variable.
df1 = None
if df1 is not None:
print df1.head()
选项2
Option 2
但是，设置一个空的数据框并不是一个坏主意.
However, setting up an empty dataframe isn't at all a bad idea.
df1 = pd.DataFrame()
if not df1.empty:
print df1.head()
选项3
Option 3
只需尝试.
try:
print df1.head()
# catch when df1 is None
except AttributeError:
pass
# catch when it hasn't even been defined
except NameError:
pass
计时
df1处于初始化状态或根本不存在时
Timing
When df1 is in initialized state or doesn't exist at all
当df1是其中包含某些内容的数据框
When df1 is a dataframe with something in it
df1 = pd.DataFrame(np.arange(25).reshape(5, 5), list('ABCDE'), list('abcde'))
df1
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