pandas Python - 输入包含 NaN、无穷大或对于 dtype('float64') 来说太大的值
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Python - Input contains NaN, infinity or a value too large for dtype('float64')
提问by Mitch
I am new on Python. I am trying to use sklearn.cluster. Here is my code:
我是 Python 新手。我正在尝试使用 sklearn.cluster。这是我的代码：
from sklearn.cluster import MiniBatchKMeans
kmeans=MiniBatchKMeans(n_clusters=2)
kmeans.fit(df)
But I get the following error:
但我收到以下错误：
50 and not np.isfinite(X).all()):
51 raise ValueError("Input contains NaN, infinity"
---> 52 " or a value too large for %r." % X.dtype)
ValueError: Input contains NaN, infinity or a value too large for dtype('float64')
I checked that the there is no Nan or infinity value. So there is only one option left. However, my data info tells me that all variables are float64, so I don't understand where the problem comes from.
我检查过没有 Nan 或无穷大值。所以只剩下一种选择了。但是，我的数据信息告诉我所有变量都是 float64，所以我不明白问题出在哪里。
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 362358 entries, 135 to 4747145
Data columns (total 8 columns):
User 362358 non-null float64
Hour 362352 non-null float64
Minute 362352 non-null float64
Day 362352 non-null float64
Month 362352 non-null float64
Year 362352 non-null float64
Latitude 362352 non-null float64
Longitude 362352 non-null float64
dtypes: float64(8)
memory usage: 24.9 MB
Thanks a lot,
非常感谢，
回答by David Maust
By looking at your df.info(), it appears that there are 6 more non-null Users values than there are values of any other column. This would indicate that you have 6 nulls in each of the other columns, and that is the reason for the error.
通过查看您的df.info()，似乎比任何其他列的值多 6 个非空用户值。这表明您在其他每一列中都有 6 个空值，这就是错误的原因。
<class 'pandas.core.frame.DataFrame'>
Int64Index: 362358 entries, 135 to 4747145
Data columns (total 8 columns):
User 362358 non-null float64
Hour 362352 non-null float64
Minute 362352 non-null float64
Day 362352 non-null float64
Month 362352 non-null float64
Year 362352 non-null float64
Latitude 362352 non-null float64
Longitude 362352 non-null float64
dtypes: float64(8)
memory usage: 24.9 MB
回答by Fabio Lamanna
I think that fit()accepts only "array-like, shape = [n_samples, n_features]", not pandas dataframes. So try to pass the values of the dataframe into it as:
我认为fit()只接受“类似数组，形状 = [n_samples, n_features]”，而不是 Pandas 数据帧。所以尝试将数据帧的值传递给它：
kmeans=MiniBatchKMeans(n_clusters=2)
kmeans.fit(df.values)
Or shape them in order to run the function correctly. Hope that helps.
或者塑造它们以正确运行功能。希望有帮助。
回答by Max Kleiner
By looking at your df.info(), it appears that there are 6 more non-null Users values than there are values of any other column. This would indicate that you have 6 nulls in each of the other columns, and that is the reason for the error.
通过查看您的 df.info()，似乎比任何其他列的值多 6 个非空用户值。这表明您在其他每一列中都有 6 个空值，这就是错误的原因。
So you can slice your data to the right fit with iloc():
因此，您可以使用 iloc() 将数据切片到合适的位置：
df = pd.read_csv(location1, encoding = "ISO-8859-1").iloc[2:20]
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 18 entries, 2 to 19
Data columns (total 6 columns):
zip_code 18 non-null int64
latitude 18 non-null float64
longitude 18 non-null float64
city 18 non-null object
state 18 non-null object
county 18 non-null object
dtypes: float64(2), int64(1), object(3)
