defmean_change(x):x = np.asarray(x)return(x[-1] - x[0]) / (len(x) -1)iflen(x) >1elsenp.NaN defmean_second_derivative_central(x):x = np.asarray(x)return(x[-1] - x[-2] - x[1] + x[0]) / (2* (len(x) -2))if...
stat_data = pd.concat([stat_data.tail(1), lr], axis=1) stat_data.insert(0, 'code', stock_code) stat_data = stat_data.set_index('code') # 导出数据到CSV文件 csv_filename = f'{stock_code}_stat_data.csv' stat_data.to_csv(csv_filename) return stat_data def get_sqlite3(): ...
Senkou Span A (Leading Span A): (Conversion Line + Base Line)/2)) Thisisthe midpoint between the Conversion Lineandthe Base Line. The Leading Span A forms one of the two Cloud boundaries. Itisreferred toas"Leading"because itisplotted26periodsinthe futureandforms the faster Cloud boundary. ...
from sklearn.linear_model import LinearRegression # 计算强弱得分 def calculate_score(srs, N=25): if srs.shape[0] < N: return np.nan x = np.arange(1, N+1) y = srs.values / srs.values[0] lr = LinearRegression().fit(x.reshape(-1, 1), y) # 斜率 slope = lr.coef_[0] # ...
1 class Entity: 2 '''Class to represent an entity. Callable to update the entity's position.''' 3 4 def __init__(self, size, x, y): 5 self.x, self.y = x, y 6 self.size = size 7 8 def __call__(self, x, y): 9 '''Change the position of the entity.''' 10 self...
to_replace:要替换的数据 value:新值 inplace:是否替换原始数据框架 注意,还可以使用其他参数,但我暂不讨论它们。有关完整的参数列表,可以查看pandas官方文档 全部替换 在Excel中,我们可以按Ctrl+H并替换所有值,让我们在这里实现相同的操作。我们使用“Yui Ikari”替换数据框架中的所有的“Ayanami Rei”。注意,对于...
>>> tuple1[0]=5 Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: 'tuple' object does not support item assignment#报错 1. 2. 3. 4. 5. Python Copy 2.2.9 变量 AI检测代码解析 a=1+1 #这里a就是一个变量,用来存储 1+1产生的2 ...
DataFrame.combine(other,func[,fill_value, …]) #Add two DataFrame objects and do not propagate NaN values, so if for a DataFrame.combine_first(other) #Combine two DataFrame objects and default to non-null values in frame calling the method. ...
"toy": [np.nan,'Batmobile','Bullwhip'], "born": [pd.NaT, pd.Timestamp("1940-04-25"), pd.NaT]}) 然后让我们尝试用下面的代码做一个简单的 pandas 操作记录。 withpandas_log.enable(): res = (df.drop("born", axis =1) .groupby('name')...
to_csv bool at clip radd to_markdown value_counts first isna between_time replace sample idxmin div iloc add_suffix pipe to_sql items max rsub flags sem to_string to_excel prod fillna backfill align pct_change expanding nsmallest append attrs rmod bfill ndim rank floordiv unstack groupby ...