ValueError: 时间数据 '2021-07-19 11:48:03.357+00'与格式 '%Y-%m-%d %H:%M:%S.%f%Z' 不匹配（匹配）
请帮忙。你能让我知道我定义的格式有什么问题吗？
from sklearn.ensemble import GradientBoostingRegressor
df = pd.read_csv('timeseries.csv')
df.head()
df['timestamp'] = pd.to_datetime(df['timestamp'], format='%Y-%m-%d %H:%M:%S.%f%Z')
X = df['timestamp']
y = df['time_minutes']
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
reg = GradientBoostingRegressor(random_state=0)
reg.fit(X_train, y_train)
GradientBoostingRegressor(random_state=0)
reg.predict(X_test[1:2])
reg.score(X_test, y_test)
ValueError：时间数据“2021-07-19 11:48:03.357+00”与格式“%Y-%m-%d %H:%M:%S.%f%Z”不匹配（匹配）
Help please. Can you let me know what's wrong with my format defined?
from sklearn.ensemble import GradientBoostingRegressor
df = pd.read_csv('timeseries.csv')
df.head()
df['timestamp'] = pd.to_datetime(df['timestamp'], format='%Y-%m-%d %H:%M:%S.%f%Z')
X = df['timestamp']
y = df['time_minutes']
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)
reg = GradientBoostingRegressor(random_state=0)
reg.fit(X_train, y_train)
GradientBoostingRegressor(random_state=0)
reg.predict(X_test[1:2])
reg.score(X_test, y_test)
ValueError: time data '2021-07-19 11:48:03.357+00' does not match format '%Y-%m-%d %H:%M:%S.%f%Z' (match)
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当你加载 csv 文件时，pandas 应该很容易处理这个问题，并且你不需要稍后解析它：
pandas should take care of that easily when you load your csv file, and you don't need to parse it later on :