bkamapantula

Source data for 26th June vaccination doses.

bkamapantula

Setup

pytchat

Install pytchat which does bulk of the work. Open a terminal and run the below to install pytchat.

pip install pytchat

bkamapantula

"""
Add several CSV files as Delimited Text Layer(s) with x coordinate as Longitude and y as Lattitude.

This script is adapted from https://chris35wills.github.io/multi_csv_into_qgis/.
Updated `addAttributeAlias` to `setFieldAlias` as it's renamed.
"""

import os.path, glob

layers = []

bkamapantula

{
  "$schema": "https://vega.github.io/schema/vega/v5.json",
  "padding": 5,
  "width": 400,
  "height": 300,
  "data": [
    {
      "name": "table",
      "url": "https://raw.githubusercontent.com/deldersveld/topojson/master/countries/france/fr-departments.json",
      "format": {"type": "topojson", "feature": "FRA_adm2"}

bkamapantula

{
  "$schema": "https://vega.github.io/schema/vega-lite/v2.4.json",
  "description": "Bar chart with text labels. Apply scale padding to make the frame cover the labels.",
  "data": {
    "values": [
      {"Metrics": "A1", "Percentage": 0.79},
      {"Metrics": "A2", "Percentage": 0.0399},
      {"Metrics": "A3", "Percentage": 0.9868},
      {"Metrics": "A4", "Percentage": 0.0536},
      {"Metrics": "A5", "Percentage": 0.9412},

bkamapantula

Kibana with nginx logs

I wanted to explore Kibana to analyze nginx logs. Finding the right place to work with data seemed unnecessarily complex.

I had to visit Visualization under Machine Learning to upload a file!

1. Cloning sample dataset for quick views is easy.
2. Importing data files into Kibana is a breeze.
3. We capture timestamp in nginx logs. But Kibana seemed to have trouble recognizing it and picking a right timestamp format.

bkamapantula

Horizontal bar chart

bkamapantula

New chart

bkamapantula

New chart

bkamapantula

New chart