pandas 将数据框转换为列表列表
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/42092585/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
convert dataframe to list of lists
提问by lolix
I have this dataframe:
我有这个数据框：
value
time
2016-12-01 00:00:00 NaN
2016-12-01 00:01:00 2
2016-12-01 00:02:00 1
I want convert this dataframe to a list of lists, likes this:
我想将此数据框转换为列表列表，如下所示：
[['2016-12-01 00:00:00', NaN],['2016-12-01 00:01:00', 2],['2016-12-01 00:02:00', 1]]
I tried df.valuesor df.values.tolist()and always receive:
我尝试df.values或df.values.tolist()总是收到：
[[ nan]
[ 2]
[ 1]]
回答by EdChum
If you call reset_indexto restore the index, you can then call .values.tolist()to get the desired result:
如果调用reset_index恢复索引，则可以调用.values.tolist()得到想要的结果：
In [117]:
df.reset_index().values.tolist()
Out[117]:
[['2016-12-01 00:00:00', nan],
['2016-12-01 00:01:00', 2.0],
['2016-12-01 00:02:00', 1.0]]
valuesreturns a numpy array, this has a method tolist()to convert to a list of lists
回答by jezrael
Need DataFrame.reset_indexfirst, DataFrame.valuesreturn numpy arrayand tolist()convert it to nested list:
极品DataFrame.reset_index第一，DataFrame.values回报numpy array和tolist()其转换为nested list：
print (df.index)
Index(['2016-12-01 00:00:00', '2016-12-01 00:01:00', '2016-12-01 00:02:00'],
dtype='object', name='time')
print (df.reset_index().values.tolist())
[['2016-12-01 00:00:00', nan], ['2016-12-01 00:01:00', 2.0], ['2016-12-01 00:02:00', 1.0]]
But if DatetimeIndexis necessary convert indexto stringby astype:
但是，如果DatetimeIndex有必要转换index到string通过astype：
print (df.index)
DatetimeIndex(['2016-12-01 00:00:00', '2016-12-01 00:01:00',
'2016-12-01 00:02:00'],
dtype='datetime64[ns]', name='time', freq=None)
print (df.reset_index().values.tolist())
[[Timestamp('2016-12-01 00:00:00'), nan],
[Timestamp('2016-12-01 00:01:00'), 2.0],
[Timestamp('2016-12-01 00:02:00'), 1.0]]
df.index = df.index.astype(str)
print (df.reset_index().values.tolist())
[['2016-12-01 00:00:00', nan], ['2016-12-01 00:01:00', 2.0], ['2016-12-01 00:02:00', 1.0]]
