结果显示,在分组和聚合计算方面,Polars的表现优于Pandas。Polars的语法与Pandas非常相似。 滚动统计测试 另一个有趣的操作是滚动统计。这涉及到复杂的计算,并且对其进行优化是一个挑战。让我们看看Pandas和Polars如何处理按天计算销售额的滚动均值。 # Pandas rolling mean df_pd['sales'].rolling(1440, min_periods=...
What are the differences in syntax that may trip you up? Here are some tips that may be useful: Selecting and filteringCopy heading link In pandas, we use.loc/.ilocand[]to select part of the data in a data frame. However, in Polars, we use.selectto do so. For example, in pandasd...
Pandas with talib %%timeit df["sma5"] = df.groupby("Ticker")["close"].transform(lambda x: ta.SMA(x, timeperiod=5)) df["macd"] = df.groupby("Ticker")["close"].transform(lambda x: ta.MACD(x, fastperiod=10, slowperiod=20, signalperiod=5)[0]) df["macdsignal"] = df.groupby...
col("close").ta.wclprice("high", "low").alias("wclprice"), ) multiple symbol usage using over syntax df.with_columns( pl.col("close").ta.ema(5).over("symbol").alias("ema5"), pl.col("close").ta.macd(12, 26, 9).over("symbol").struct.field("macd"), pl.col("close")....