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Pandas Dataframe Methods
Pandas DataFrames are the cornerstone of data manipulation, offering an extensive suite of methods for effective data analysis. It deals with methods like merge() to merge datasets, groupby() to group data for analysis and pivot() to pivot tables for better insights.
NumPy std()
std() computes standard deviation of given numbers
NumPy percentile()
percentile() computes q-th percentile of the data
NumPy max()
max() returns the largest element of an array
NumPy min()
min() returns the smallest element of an array.
NumPy average()
average() computes the weighted average of array
NumPy correlate()
computes cross-correlation of two 1D sequences
NumPy median()
median() finds the median along specified axis.
NumPy var()
var() computes the variance along specified axis
NumPy quantile()
quantile() computes the q-th quantile of the data
NumPy nanmean()
nanmean() computes arithmetic mean, ignoring NaNs
NumPy ptp()
computes range of values(maximum-minimum) in array
NumPy cov()
estimate covariance matrix, given data and weights
NumPy mean()
mean() computes arithmetic mean of a given set