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ShankarravanakiShankarravanaki
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14/06/2023
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‎Module1/Python string methods.ipynb

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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Python String methods"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Shankar\n",
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"SHANKAR\n"
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]
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}
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],
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"source": [
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"s1=(\"shankar\")\n",
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"print(s1.capitalize()) # first letter only calpitalize\n",
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"print(s1.upper()) # all letters should capital\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"shankar\n"
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]
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}
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],
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"source": [
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"s1=(\"SHANKAR\")\n",
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"print(s1.lower()) # all leter should lower letter\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"**Shankar**\n"
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]
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}
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],
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"source": [
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"s1=(\"Shankar\")\n",
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"print(s1.center(11,'*')) # head line writen using str *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n"
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]
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}
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],
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"source": [
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"s3=(\" WELLCOME HELLO WORLD\")\n",
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"print(s3.count(\"L\")) # count the Selecting letters "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"10\n"
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]
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}
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],
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"source": [
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"s3=(\" WELLCOME HELLO WORLD\")\n",
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"print(s3.index('H')) # Find the index number of letter"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 48,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"-1\n"
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]
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}
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],
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"source": [
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"s3=(\"HELLOWORLD\")\n",
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"print(s3.find('LR'))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"14-06-2023\n"
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]
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}
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],
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"source": [
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"str=(\"14/06/2023\")\n",
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"print(str.replace('/','-')) # replace the sign ,Numbers ,and letters"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['14', '06', '2023']\n"
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]
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}
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],
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"source": [
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"str=(\"14/06/2023\")\n",
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"print(str.split('/')) # split the numbers "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 70,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n",
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"False\n"
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]
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}
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],
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"source": [
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"str1=('12345')\n",
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"print(str1.isnumeric()) # print only number \n",
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"str1=('avdf')\n",
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"print(str1.isnumeric())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 69,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n",
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"False\n"
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]
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}
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],
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"source": [
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"str1=('1a')\n",
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"print(str1.isalnum()) # print only alphabet and number\n",
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"str1=('1./')\n",
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"print(str1.isalnum())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 68,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n",
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"False\n"
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]
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}
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],
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"source": [
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"str1=('SHANKAR')\n",
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"print(str1.isupper())\n",
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"\n",
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"str1=('SHANKAr')\n",
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"print(str1.isupper())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 72,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"False\n",
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"True\n"
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]
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}
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],
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"source": [
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"str1=('Shankar')\n",
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"print(str1.islower())\n",
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"\n",
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"str1=('shankar')\n",
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"print(str1.islower())"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.3"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎Statistical Learning.ipynb renamed to ‎Module3/Statistical Learning.ipynb

File renamed without changes.

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