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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 arange()
creates an array with interval-based elements
NumPy zeros()
creates new array of given shape filled with zeros
NumPy linspace()
create evenly spaced array elements over interval
NumPy ones()
creates new array of given shape filled with ones
NumPy ones()
creates new array of given shape filled with ones
NumPy logspace()
logspace() creates array with evenly spaced number
NumPy meshgrid()
meshgrid() taken 1D arrays and returns 2D arrays
NumPy empty()
empty() creates new array without defining entries
NumPy copy()
copy() returns the copy of an array
NumPy full()
full() creates an array filled with a given value
NumPy loadtxt()
loadtxt() loads data from a text file
NumPy asarray()
asarray() converts all array-like objects to array
NumPy diag()
diag() either forms or fetches diagonal of array
NumPy eye()
eye() creates 2D array with 1s(on diagonal) and 0s
NumPy frombuffer()
frombuffer() interprets a buffer as a 1D array