【发布时间】:2021-04-04 00:51:09
【问题描述】:
我正在为特定数据集创建线性回归模型,我正在按照我在你的电子管上找到的示例进行操作,有时我会计算峰度和偏度,如下所示:
# calculate the excess kurtosis using the fisher method. The alternative is Pearson which
calculates regular kurtosis.
exxon_kurtosis = kurtosis(price_data['exxon_price'], fisher = True)
oil_kurtosis = kurtosis(price_data['oil_price'], fisher = True)
# calculate the skewness
exxon_skew = skew(price_data['exxon_price'])
oil_skew = skew(price_data['oil_price'])
display("Exxon Excess Kurtosis: {:.2}".format(exxon_kurtosis)) # this looks fine
display("Oil Excess Kurtosis: {:.2}".format(oil_kurtosis)) # this looks fine
display("Exxon Skew: {:.2}".format(exxon_skew)) # moderately skewed
display("Oil Skew: {:.2}".format(oil_skew)) # moderately skewed, it's a
little high but we will accept it.
我是python新手,下面的代码让我很困惑{:.2},请有人解释一下这部分{:.2}
display("Exxon Excess Kurtosis: {:.2}".format(exxon_kurtosis))
【问题讨论】:
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具有 2 个有效数字的浮点数。