Outlier Detection on Time Series Data using Pandas
In this post we will look several ways to visualize and extract time series data with the help of Pandas.
Cross Tabulation in Pandas
The data Importing the Library and loading the data Crosstab Basic Selection with .loc and .iloc Using basic function with cross tab Margins are for total Normalizing Results Aggregate function Sorting Unique values Visualization Plotting
Interactive Map in Python
Task: To plot all hydros of district with max hydro in province 6, Nepal Installing library Importing library Reading data of hydro powers Libraries for visualization Basic map Map with layers Map with hydros in Jajarkot with markers
Plotting map in Python
https://www.nationalgeoportal.gov.np/#/metadata/98 installing required libraries Importing libraries Read The province data Plotting map Boundaries Centroid of all province Area wise colormap plot of all province
Data Exploring And Analysis
Exploring and Analyzing a Series Operation on a Series Exploring and Analyzing a Data Frame Data Grouping Data Aggregation Filtration
Data Gathering and Cleaning
Checking and Handling Missing Values Reading and Cleaning CSV data Using functions to clean data Merging and Integrating Data Data for following section
DataFrame in Pandas
A data frame is a two-dimensional tabular labeled data structure with columns of potentially different types. A data frame can be created from numerous data collections such as the following: A 1D ndarray, list, dict, or series 2D Numpy ndarray Structured or record ndarray A series Another data frame A data frame has arguments, which are an index (row labels) […]
Series in Pandas
Creating a series Output Create list from dictionary Creating Series using a Scalar Accessing a Data in Series Exploring and Analyzing a Series