Pandas is an open-source data analysis library that is based on Python language. For more refer to our detailed article: What is Pandas Library?
Pandas was first released on 11 January 2008. It was written by Wes McKinney (an American Software Developer). For Pandas Version and History, read our detailed article: Pandas History and Versions.
Pandas is written using Python, CPython, and C language.
Pandas Provide Three major data structures:
Series - It is immutable in size and homogeneous one-dimensional array data structure.
DataFrame - It is a tabular data structure that comprises rows and columns. Here, data and size are mutable.
Panel - It is a three-dimensional data structure to store the data heterogeneously.
It is a concept of performing array/list operations without using loops. Instead, use built-in functions which are highly optimized and reduce the running and execution time of code.
We can convert dataframe data to list by using the list() or tolist() function. For more details, refer to this detailed article: Convert Dataframe to List.
cov()
corr()
rank()
sum()
mean()
std()
describe()
We can create Dataframe from several data containers such as:
Dictionary
File
NumPy Array
For more, read this detailed article: Create Dataframe in Pandas.
Yes, we can create an empty dataframe by using some built-in functions of Pandas such as Pandas.dataframe() function. For detailed information, read this Create an empty datafame.
You can add columns to dataframe by using several built-in functions such as the insert() and assign() function. For detailed information, read this add new column to dataframe.
To rename dataframe columns, we can use these methos:
dataframe.columns attribute/property
dataframe.rename() method
For more information, read this detailed article: rename dataframe column.
We can iterate pandas by using loops and some built-in methods such as:
iterrows() Function
itertuples() Function
range() Function + iloc[]
for loop
apply() Function
For more, refer to this detailed article: Iterate Dataframe.
We will add more questions soon...