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This repo contains my Python learning from basic to data science, featuring basic programming, logic building, data manipulation, analysis, and visualization. Stay tuned for updates and new content!\n\n### **Learning/Quick-Notes:**  \n-     #Use of random module\n      import random\n      r = random.randint(1, 10)\n      print(r)\n\n-     #Use of calendar module\n      import calendar\n      y = int(input(\"Enter the year: \"))\n      m = int(input(\"Enter the month: \"))\n      c = calendar.month(y, m)\n      print(c)\n\n-     #Use of math module\n      import math\n      print(math.sqrt(25))\n\n-     #Use of format() funn\n      print(\"{0} is Prime number\".format(n))\n\n-     #Binary, Octal, Hexadecimal funn: convert decimal -\u003e binary, octal, hexadecimal\n      bin(), oct(), hex()\n\n-     #ASCII: Character -\u003e ASCII number {funn}\n      ord()\n\n-     # Data Collection\n      data = []\n      data.extend([10, 20, 30, 40, 50])\n\n      # Data Cleaning\n      if 30 in data:\n            data.remove(30)\n\n      # Data Transformation\n      data.sort()\n      data.reverse()\n\n      # Data Summarization\n      total = sum(data)\n      max_value = max(data)\n      min_value = min(data)\n\n      # Preparing for Visualization\n      indexed_data = list(enumerate(data))\n\n      print(\"Cleaned Data:\", data)\n      print(\"Total:\", total)\n      print(\"Max Value:\", max_value)\n      print(\"Min Value:\", min_value)\n      print(\"Indexed Data:\", indexed_data)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiankitnegi%2Fdatapy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fiankitnegi%2Fdatapy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fiankitnegi%2Fdatapy/lists"}