cal=calendar.month(year, month) lines= cal.split("\n") ch_lines=[ch_week_names[:]]forlineinlines[2:]:#跳过前两行非日期信息ch_lines.append([iifi !=""else""foriinline.split()])returnch_month_names[month - 1], ch_linesprint()#获取当前年月now =datetime.now() year, month=now.ye...
names:List[str]=["li","tom"]version:Tuple[int,int,int]=(6,6,6)operations:Dict[str,bool]={'sad':False,'happy':True} List List[int]表示由整型组成的列表,比如[0, 1, 1, 2, 3], var: List[str] = ['abc','def'] var: List[int or float] = [2, 3.5] var: List[List[int]]...
xgb_predictions[tgt])eli5.show_prediction(xgb.get_booster(),X_test.iloc[tgt],feature_names=list(data.columns),show_feature_values=True)###%%time# 需要用数组重新训练一个新模型# eli5在Dataframes和XGBoost方面有一个bug#
import re # 正则表达式库import jieba # 结巴分词 import jieba.posseg # 词性获取 import collections # 词频统计库 import numpy # numpy数据处理库seg_list_exact = jieba.cut(string_data, cut_all=False, HMM=True) # 精确模式分词+HMM jieba.load_userdict("词典.txt") # 批量添加词典,utf-8编码 wi...
Unit Root Test Thenullhypothesisofthe Augmented Dickey-Fuller is that there is a unit root,withthe alternative that there is no unit root.That is to say the bigger the p-value the more reason we assert that there is a unit root''' def testStationarity(ts): dftest = adfuller(ts) # ...
pd.get_dummies( df, # columns是list columns=['Gender'], # prefix可以使字符串,或者是字符串列表 prefix='Gender1', prefix_sep='_', dummy_na= False, # 默认用False,原因我也不知道啊。。 drop_first= False ) #在使用get_dummies()时,是在原列的基础上进行修改,需要将原来的Gender列重新赋值...
必须要输入一个元组作为参数。如果你恰巧有一个 list 或者 set 类型的选择项,要确保传递参数前先调用 tuple() 将其转换为元组类型 类似的操作也可以使用切片来实现,但是代码看起来没有那么优雅 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>>filename='spam.txt'>>>filename[-4:]=='.txt'True>>...
_get_label_or_level_values(lk)) 1019 join_names.append(lk) 1020 else: /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/pandas/core/generic.py in _get_label_or_level_values(self, key, axis) 1561 values = self.axes[axis].get_level_values(key)._values 1562 else: ...
Update( values=None, # 元祖或者列表,举例如下 # values=[1,3] # values=(1,3) disabled=None, # bool : 更新元素是否禁用,举例如下 # disabled=True # disabled=False set_to_index=None, # 高亮显示设定的索引,Union[int, list, tuple],举例如下 # set_to_index=1 # set_to_index=[1,2] #...
(1, 1) forecast_data = forecast_next_day_data(model, type='month') forecast_list.append(forecast_data) add_today_data(model, ts_train, dta, [12, 1], type='month') predict_ts = pd.Series(data=forecast_list, index=ts['1957-1':].index) log_recover = np.exp(predict_ts)original...