act_report.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Report: act_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": false,
    "tags": [
     "hide-input"
    ],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "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>tweet_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>dog_stages</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>...</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>668826086256599040</td>\n",
       "      <td>2015-11-23 16:18:59+00:00</td>\n",
       "      <td>Twitter for iPhone</td>\n",
       "      <td>This is Banditt. He is a brown LaBeouf retriever. Loves cold weather. 4 smaller dogs are his sons (probably). 10/10 https://t.co/Ko7eCsFpnI</td>\n",
       "      <td>https://twitter.com/dog_rates/status/668826086256599040/photo/1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Banditt</td>\n",
       "      <td>NaN</td>\n",
       "      <td>112.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Malinois</td>\n",
       "      <td>0.640185</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_terrier</td>\n",
       "      <td>0.1537</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.068457</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                  timestamp              source  \\\n",
       "0  668826086256599040  2015-11-23 16:18:59+00:00  Twitter for iPhone   \n",
       "\n",
       "                                                                                                                                          text  \\\n",
       "0  This is Banditt. He is a brown LaBeouf retriever. Loves cold weather. 4 smaller dogs are his sons (probably). 10/10 https://t.co/Ko7eCsFpnI   \n",
       "\n",
       "                                                     expanded_urls  \\\n",
       "0  https://twitter.com/dog_rates/status/668826086256599040/photo/1   \n",
       "\n",
       "   rating_numerator  rating_denominator     name dog_stages  retweet_count  \\\n",
       "0              10.0                10.0  Banditt        NaN          112.0   \n",
       "\n",
       "   ...  img_num        p1   p1_conf  p1_dog             p2  p2_conf p2_dog  \\\n",
       "0  ...      1.0  Malinois  0.640185    True  Irish_terrier   0.1537   True   \n",
       "\n",
       "                    p3   p3_conf p3_dog  \n",
       "0  Rhodesian_ridgeback  0.068457   True  \n",
       "\n",
       "[1 rows x 23 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive_master = pd.read_csv('twitter_archive_master.csv')\n",
    "twitter_archive_master.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Analyzing and Visualizing Data\n",
    "In this section, we analyze and visualize our wrangled data. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "1. What is the correlation betweeen retweet_count and favorite_count\n",
    "2. correlation betweenNumerator rating and likes?\n",
    "3. Correlation between 'retweet_count','favorite_count', 'rating_numerator'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "### Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1. What is the correlation betweeen retweet_count and favorite_count\n",
    "#plots a scatter plot to display the correlation between favorite_count and retweet_count\n",
    "sns.scatterplot(data=twitter_archive_master, x='favorite_count', y='retweet_count').set(title = 'correlation betweet retweet_count, and favorite-count')\n",
    "sns.set(rc={'figure.figsize':(15, 10)})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "The above scatter plot shows that there is a positive correlation between retweet_counts and favorite_counts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Variables Correlation')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(twitter_archive_master[['retweet_count','favorite_count', 'rating_numerator']].corr(), cmap=\"plasma_r\", annot=True)\n",
    "plt.title('Variables Correlation', size=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "strongest correlation is between retweet_count and and favorite count having a correlation coefficient of 0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "tags": [
     "hide-input"
    ],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2. let's plot the ratings that are less than 20\n",
    "plt.hist(twitter_archive_master.rating_numerator[twitter_archive_master.rating_numerator <= 17], \n",
    "         bins=np.arange(0,18,step=1), align='left');\n",
    "plt.xticks(np.arange(0,18,step=1));\n",
    "plt.title('Ratings Between 0 and 17 (all /10)');\n",
    "plt.xlabel('Rating Numerator');\n",
    "plt.ylabel('Count');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "The bar chart above shows dogs with ratings numerator of between 10-12 have the most likes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "tags": [
     "hide-input"
    ],
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'popular dog stage distribution')]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3. bar chart of the dog_stages showing the count of the dog stage column \n",
    "sns.countplot(x = 'dog_stages', data = twitter_archive_master).set(title = 'popular dog stage distribution')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "The bar chart above shows pupper is the most popular dog stage, followed by doggo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pupper     118\n",
       "doggo       35\n",
       "puppo       14\n",
       "floofer      5\n",
       "Name: dog_stages, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive_master['dog_stages'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Twitter for iPhone     1268\n",
       "Vine - Make a Scene      41\n",
       "Twitter Web Client       16\n",
       "TweetDeck                 8\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 4. Popular source medium for twitter\n",
    "source_medium = twitter_archive_master['source'].value_counts().index\n",
    "twitter_archive_master['source'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# 4. Popular source medium for twitter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(data = twitter_archive_master, y = 'source', order = source_medium)\n",
    "plt.xticks(rotation = 360)\n",
    "plt.xlabel('Count', fontsize=14)\n",
    "plt.ylabel('Source', fontsize=14)\n",
    "plt.title('The Distribution of Source',fontsize=16);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "Its clearly observed that twitter for iphone was widely used medium that individuals used to access and rate the dogs. Subsequently followed by Vine, Twitter Web Client, TweetDeck.\n",
    "\n",
    "    - (TweetDeck is a social media dashboard application for management of Twitter accounts. Originally an independent app, TweetDeck was subsequently acquired by Twitter Inc. and integrated into Twitter's interface. It has long ranked as one of the most popular Twitter clients by percentage of tweets posted, alongside the official Twitter web client and the official apps for iPhone and Android.) [https://en.wikipedia.org/wiki/TweetDeck]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}