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