Question

我有一个包含

的数据框

user_id    date       browser  conversion  test  sex  age  country
   1    2015-12-03       IE        1         0    M   32.0   US

到目前为止，这是我的整个代码！

data["country"].fillna("missing")
data["age"].fillna(-10000, inplace=True)
data["ads_channel"].fillna("missing")
data["sex"].fillna("missing")
data['date'] = pd.to_datetime(data.date)

columns = data.columns.tolist()
columns = [c for c in columns if c not in ["test"]]
from sklearn import tree
clf = tree.DecisionTreeClassifier(max_depth=2, min_samples_leaf = (len(data)/100) )
clf = clf.fit(data[columns],data["test"])

我收到此错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-560-95a8a54aa939> in <module>()
      4 from sklearn import tree
      5 clf = tree.DecisionTreeClassifier(max_depth=2, min_samples_leaf = (len(data)/100) )
----> 6 clf = clf.fit(data[columns],data["test"])

C:\Users\SnehaPriya\Anaconda2\lib\site-packages\sklearn\tree\tree.pyc in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
    152         random_state = check_random_state(self.random_state)
    153         if check_input:
--> 154             X = check_array(X, dtype=DTYPE, accept_sparse="csc")
    155             if issparse(X):
    156                 X.sort_indices()

C:\Users\SnehaPriya\Anaconda2\lib\site-packages\sklearn\utils\validation.pyc in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
    371                                       force_all_finite)
    372     else:
--> 373         array = np.array(array, dtype=dtype, order=order, copy=copy)
    374 
    375         if ensure_2d:

TypeError: float() argument must be a string or a number

我仍在学习编码，我想知道如何克服这个错误。任何帮助将不胜感激！

Answer 1

IIUC您还需要排除列date：

columns = [c for c in columns if c not in ["test", 'date']]

因为错误：

TypeError：float（）参数必须是字符串或数字，而不是＆＃39;时间戳＆＃39;

Answer 2

保留日期（时间）列的解决方案：

data['date'] = pd.to_numeric(pd.to_datetime(data['date']))

Pandas：TypeError：float（）参数必须是字符串或数字

2 个答案: