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What this article shares with you is about what statistical functions are described in Pandas. The editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article.

In the statistical description, pandas specifies the axis parameters of the three data objects as follows:

Series: no axis parameter

DataFrame: "index" (axis=0, default), "columns" (axis=1)

Panel: "items" (axis=0), "major" (axis=1, default), "minor" (axis=2)

The statistical description parameters are as follows:

FunctionDescription describes the number of countNumber of non-null observations observations sumSum of values and meanMean of values calculates the average madMean absolute deviation average absolute variance medianArithmetic median of values median maxMaximum maximum modeMode mode absAbsolute Value absolute value prodProduct of values product stdBessel-corrected sample standard deviation variance semStandard error of the mean standard error skewSample skewness (3rd moment) skewness coefficient kurtSample kurtosis (4th moment) kurtosis quantileSample quantile (value at%) quartile cumsumCumulative sum cumulative cumprodCumulative product Multiply cummaxCumulative maximum maximum cumminCumulative minimum minimum cov () covariance covariance corr () correlation correlation coefficient rank () rank by values ranking pct_change () time change time series changes above are the descriptive statistical functions in Pandas The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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