我收到以下TypeError：
TypeError: Cannot cast array data from dtype('<M8[ns]') to dtype('float64') according to the rule 'safe'
原因似乎与该部分有关：
X = event_data.index.values.reshape(-1,1)
您在这里看到我做错了吗？ Here指向我的数据的链接。
from sklearn import linear_model
def load_event_data():
df = pd.read_csv('sample-data.csv', usecols=['created', 'total_gross'])
df['created'] = pd.to_datetime(df.created)
return df.set_index('created').resample('D').sum().fillna(0)
event_data = load_event_data()
event_data['total_gross_accumulated'] = event_data['total_gross'].cumsum()
print(event_data.index.dtype)
event_data.head()
# Explore data
X = event_data.index
y = event_data['total_gross_accumulated']
plt.xticks(rotation=90)
plt.plot(X, y)
plt.show()
# Create and Fit a Linear Regression Model
regr = linear_model.LinearRegression()
# Reshape X
X = event_data.index.values.reshape(-1,1)
regr.fit(X, y)
y_predict = regr.predict(X)
# Show data and prediction
plt.plot(X, y)
plt.plot(X, y_predict)
plt.show()