project5plotterr.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import plotly as pl\n",
    "import plotly.offline as po\n",
    "import cufflinks as cf\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "po.init_notebook_mode(connected=True)\n",
    "cf.go_offline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def createdata(data):\n",
    "    if (data==1):\n",
    "        row=int(input(\"Enter the rows:\"))\n",
    "        column=int(input(\"Enter the columns\"))\n",
    "        \n",
    "        x = np.random.rand(row,column)\n",
    "        df2 = pd.DataFrame(x)\n",
    "    elif (data==2):\n",
    "        x1=[]\n",
    "        r1=[]\n",
    "        r2=[]\n",
    "        r3=[]\n",
    "        r4=[]\n",
    "        n=int(input(\"How many columns you want(note:type value not string):\"))\n",
    "        for i in range(n):\n",
    "            x1.append(input(\"Enter Column(note:type string):\"))\n",
    "            \n",
    "        print(\"Enter the values of First row:\")\n",
    "        i=0\n",
    "        for i in range(n):\n",
    "            r1.append(int(input(\"Enter row(note:type value):\")))\n",
    "        i=0\n",
    "        print(\"Enter the values of Second row:\")\n",
    "        i=0\n",
    "        for i in range(n):\n",
    "            r2.append(int(input(\"Enter row(note:type value):\")))\n",
    "        \n",
    "        print(\"Enter the values of Thrid row:\")\n",
    "        i=0\n",
    "        for i in range(n):\n",
    "            r3.append(int(input(\"Enter row(note:type value):\")))\n",
    "        \n",
    "        print(\"Enter the values of Fourth row:\")\n",
    "        i=0\n",
    "        for i in range(n):\n",
    "            r4.append(int(input(\"Enter row(note:type value):\")))\n",
    "        \n",
    "        df2 = pd.DataFrame([r1,r2,r3,r4], columns=x1)\n",
    "    elif(data==3):\n",
    "        file = input(\"Enter the name your file with type:\")\n",
    "        x = pd.read_csv(file)\n",
    "        df2 = pd.DataFrame(x)\n",
    "    else:\n",
    "        print(\"DataFrame Creation Failed! DataFrame Creation Failed! Choose Correct Option 1,2 or 3 and try again:\")\n",
    "    return df2    \n",
    "    \n",
    "        \n",
    "        \n",
    "        \n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plotter(plot):\n",
    "    \n",
    "    if (plot==1):\n",
    "        finalplot = df2.iplot(kind=\"scatter\")\n",
    "    elif (plot==2):\n",
    "        finalplot = df2.iplot(kind=\"scatter\",mode='markers',symbol='x',colorscale='paired')\n",
    "    elif (plot==3):\n",
    "        finalplot = df2.iplot(kind=\"bar\")\n",
    "    elif (plot==4):\n",
    "        finalplot = df2.iplot(kind=\"hist\")\n",
    "    elif (plot==5):\n",
    "        finalplot = df2.iplot(kind=\"box\")\n",
    "    elif (plot==6):\n",
    "        finalplot = df2.iplot(kind=\"surface\")\n",
    "    else:\n",
    "        finalplot = print(\"Pleae enter correct option in 1 to 6 and try again..\")\n",
    "    return finalplot\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plotter2(plot):\n",
    "    col = int(input(\"Enter the number of column you want to plot by selecting only 1, 2 or 3\"))\n",
    "    if (col==1):\n",
    "        colm= input(\"Enter the column you want by selecting any column form DataFrame head:\")\n",
    "        if(plot==1):\n",
    "            finalplot= df2[colm].iplot(kind='scatter')\n",
    "        elif(plot==2):\n",
    "            finalplot= df2[colm].iplot(kind='scatter', mode='markers', symbol='x',colorscale='paired')\n",
    "        elif(plot==3):\n",
    "            finalplot= df2[colm].iplot(kind='bar')\n",
    "        elif(plot==4):\n",
    "            finalplot= df2[colm].iplot(kind='hist')\n",
    "        elif(plot==5):\n",
    "            finalplot= df2[colm].iplot(kind='box')\n",
    "        elif(plot==6 or plot==7):\n",
    "            finalplot= print(\"Surface Plot and Bubble Plot require more then one column..\")\n",
    "        else:\n",
    "            finalplot= print(\"Select Only Between 1 to 7:\")\n",
    "        return finalplot\n",
    "    elif (col==2):\n",
    "        x=input(\"First Column:\")\n",
    "        y=input(\"Second Column:\")\n",
    "        if(plot==1):\n",
    "            finalplot= df2[[x,y]].iplot(kind='scatter')\n",
    "        elif(plot==2):\n",
    "            finalplot= df2[[x,y]].iplot(kind='scatter', mode='markers', symbol='x',colorscale='paired')\n",
    "        elif(plot==3):\n",
    "            finalplot= df2[[x,y]].iplot(kind='bar')\n",
    "        elif(plot==4):\n",
    "            finalplot= df2[[x,y]].iplot(kind='hist')\n",
    "        elif(plot==5):\n",
    "            finalplot= df2[[x,y]].iplot(kind='box')\n",
    "        elif(plot==6):\n",
    "            finalplot= df2[[x,y]].iplot(kind='surface')\n",
    "        elif(plot==7):\n",
    "            size=input(\"Please enter the size column for Bubble Plot:\")\n",
    "            finalplot= df2.iplot(x=x,y=y,kind='bubble',size=size)\n",
    "            \n",
    "\n",
    "        else:\n",
    "            finalplot= print(\"Select Only Between 1 to 7:\")\n",
    "        return finalplot\n",
    "        \n",
    "\n",
    "    elif (col==3):\n",
    "        x=input(\"First Column:\")\n",
    "        y=input(\"Second Column:\")\n",
    "        z=input(\"Third Column:\")\n",
    "        if(plot==1):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='scatter')\n",
    "        elif(plot==2):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='scatter', mode='markers', symbol='x',colorscale='paired')\n",
    "        elif(plot==3):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='bar')\n",
    "        elif(plot==4):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='hist')\n",
    "        elif(plot==5):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='box')\n",
    "        elif(plot==6):\n",
    "            finalplot= df2[[x,y,z]].iplot(kind='surface')\n",
    "        elif(plot==7):\n",
    "            size=input(\"Please enter the size column for Bubble Plot:\")\n",
    "            finalplot= df2.iplot(x=x,y=y,z=z,kind='bubble',size=size)\n",
    "            \n",
    "\n",
    "        else:\n",
    "            finalplot= print(\"Select Only Between 1 to 7:\")\n",
    "        return finalplot\n",
    "\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main(cat):\n",
    "    if (cat==1):\n",
    "        print(\"Select the type of plot you want by writing 1 to 6:\")\n",
    "        print(\"1. Line Plot.\")\n",
    "        print(\"2. Scatter Plot.\")\n",
    "        print(\"3. Bar Plot.\")\n",
    "        print(\"4. Histogram Plot.\")\n",
    "        print(\"5. Box Plot.\")\n",
    "        print(\"6. Surface Plot\")\n",
    "        plot = int(input(\"Enter the option:\"))\n",
    "        output = plotter(plot)\n",
    "    elif (cat==2):\n",
    "        print(\"Select the type of plot you want by writing 1 to 7:\")\n",
    "        print(\"1. Line Plot.\")\n",
    "        print(\"2. Scatter Plot.\")\n",
    "        print(\"3. Bar Plot.\")\n",
    "        print(\"4. Histogram Plot.\")\n",
    "        print(\"5. Box Plot.\")\n",
    "        print(\"6. Surface Plot\")\n",
    "        print(\"7. Bubble Plot.\")\n",
    "        plot = int(input(\"Enter the option:\"))\n",
    "        output = plotter2(plot)\n",
    "    else:\n",
    "        print(\"Please enter correct option 1 or 2 and try again..\")\n",
    "\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Select the type of data, you need to plot (By writing 1,2 or 3):\n",
      "1. Random data with 100 row and 5 columns.\n",
      "2. Customize data frame yourself.\n",
      "3. Upload CSV/JSON/TEXT files.\n",
      "Enter option here:1\n",
      "Enter the rows:5\n",
      "Enter the columns5\n"
     ]
    }
   ],
   "source": [
    "print(\"Select the type of data, you need to plot (By writing 1,2 or 3):\")\n",
    "print(\"1. Random data with 100 row and 5 columns.\")\n",
    "print(\"2. Customize data frame yourself.\")\n",
    "print(\"3. Upload CSV/JSON/TEXT files.\")\n",
    "data = int(input(\"Enter option here:\"))\n",
    "df2 = createdata(data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your DataFrame head is given below, check the columns to plot using cufflinks..\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.170507</td>\n",
       "      <td>0.077898</td>\n",
       "      <td>0.322796</td>\n",
       "      <td>0.475932</td>\n",
       "      <td>0.293161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.885602</td>\n",
       "      <td>0.982623</td>\n",
       "      <td>0.229751</td>\n",
       "      <td>0.800990</td>\n",
       "      <td>0.480379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.535743</td>\n",
       "      <td>0.679765</td>\n",
       "      <td>0.421836</td>\n",
       "      <td>0.383102</td>\n",
       "      <td>0.254027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.634312</td>\n",
       "      <td>0.196148</td>\n",
       "      <td>0.981166</td>\n",
       "      <td>0.675164</td>\n",
       "      <td>0.328881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.815929</td>\n",
       "      <td>0.344720</td>\n",
       "      <td>0.770122</td>\n",
       "      <td>0.554052</td>\n",
       "      <td>0.455074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "          0         1         2         3         4\n",
       "0  0.170507  0.077898  0.322796  0.475932  0.293161\n",
       "1  0.885602  0.982623  0.229751  0.800990  0.480379\n",
       "2  0.535743  0.679765  0.421836  0.383102  0.254027\n",
       "3  0.634312  0.196148  0.981166  0.675164  0.328881\n",
       "4  0.815929  0.344720  0.770122  0.554052  0.455074"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Your DataFrame head is given below, check the columns to plot using cufflinks..\")\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "What kind of plot you need, the complete plot or column plot..\n",
      "Press 1 for plot all columns and Press 2 for plot specifing columns to plot:1\n"
     ]
    }
   ],
   "source": [
    "print(\"What kind of plot you need, the complete plot or column plot..\")\n",
    "cat = int(input(\"Press 1 for plot all columns and Press 2 for plot specifing columns to plot:\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Select the type of plot you want by writing 1 to 6:\n",
      "1. Line Plot.\n",
      "2. Scatter Plot.\n",
      "3. Bar Plot.\n",
      "4. Histogram Plot.\n",
      "5. Box Plot.\n",
      "6. Surface Plot\n",
      "Enter the option:4\n"
     ]
    },
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