review.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Unnamed: 0</th>\n",
       "      <th>Issue</th>\n",
       "      <th>Key</th>\n",
       "      <th>Logged</th>\n",
       "      <th>01/Nov/23</th>\n",
       "      <th>02/Nov/23</th>\n",
       "      <th>03/Nov/23</th>\n",
       "      <th>04/Nov/23</th>\n",
       "      <th>05/Nov/23</th>\n",
       "      <th>06/Nov/23</th>\n",
       "      <th>...</th>\n",
       "      <th>26/Jan/24</th>\n",
       "      <th>27/Jan/24</th>\n",
       "      <th>28/Jan/24</th>\n",
       "      <th>29/Jan/24</th>\n",
       "      <th>30/Jan/24</th>\n",
       "      <th>31/Jan/24</th>\n",
       "      <th>01/Feb/24</th>\n",
       "      <th>02/Feb/24</th>\n",
       "      <th>03/Feb/24</th>\n",
       "      <th>04/Feb/24</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>\"Phone\" field is missing in the stored members...</td>\n",
       "      <td>YGMP1-362</td>\n",
       "      <td>0.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[0.3] Deployemnt process.</td>\n",
       "      <td>YGMP1-426</td>\n",
       "      <td>0.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>[API] Add profile management for Volunteers</td>\n",
       "      <td>YGMP1-168</td>\n",
       "      <td>0.25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Unnamed: 0                                              Issue        Key  \\\n",
       "0        NaN  \"Phone\" field is missing in the stored members...  YGMP1-362   \n",
       "1        NaN                          [0.3] Deployemnt process.  YGMP1-426   \n",
       "2        NaN        [API] Add profile management for Volunteers  YGMP1-168   \n",
       "\n",
       "   Logged  01/Nov/23  02/Nov/23  03/Nov/23  04/Nov/23  05/Nov/23  06/Nov/23  \\\n",
       "0    0.75        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "1    0.25        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "2    0.25        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "   ...  26/Jan/24  27/Jan/24  28/Jan/24  29/Jan/24  30/Jan/24  31/Jan/24  \\\n",
       "0  ...        0.5        NaN        NaN       0.25        NaN        NaN   \n",
       "1  ...        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "2  ...        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "   01/Feb/24  02/Feb/24  03/Feb/24  04/Feb/24  \n",
       "0        NaN        NaN        NaN        NaN  \n",
       "1        NaN        NaN        NaN        NaN  \n",
       "2        NaN        NaN        NaN        NaN  \n",
       "\n",
       "[3 rows x 100 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"./User_Trung_Mai_01_Nov_23_04_Feb_24_Logged_Time.xls\", sheet_name=\"Report\")\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(df.tail(1).index, inplace=True)\n",
    "df.drop(\"Unnamed: 0\", axis=1, inplace=True)\n",
    "df = df.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tổng số task đã thực hiện trong thời gian qua: 219\n"
     ]
    }
   ],
   "source": [
    "print(f\"Tổng số task đã thực hiện trong thời gian qua: {df.shape[0]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "billable_df = df[df[\"Key\"].apply(lambda x: x.startswith(\"YGMP1\"))]\n",
    "ultilized_df = df[df[\"Key\"].apply(lambda x: x.startswith(\"CGR\"))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tổng số task billable: 89\n",
      "Tổng số task utilized: 176\n"
     ]
    }
   ],
   "source": [
    "print(f\"Tổng số task billable: {billable_df.shape[0]}\")\n",
    "print(f\"Tổng số task utilized: {billable_df.shape[0] + ultilized_df.shape[0]}\")"
   ]
  },
  {
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   "execution_count": 85,
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    "tasks_data[\"non-utilized\"] = len(df) - tasks_data[\"utilized\"]\n",
    "fig = go.Figure()\n",
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    "fig.update_layout(\n",
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    "    width=500,\n",
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    "fig.show()"
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   ],
   "source": [
    "tasks_data_pie = {\"billable\": billable_df.shape[0], \"utilized\": ultilized_df.shape[0]}\n",
    "tasks_data_pie[\"non-utilized\"] = len(df) - tasks_data_pie[\"utilized\"] - tasks_data_pie[\"billable\"]\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Pie(labels=list(tasks_data_pie.keys()), values=list(tasks_data_pie.values()),\n",
    "                     textinfo='label+percent', pull=[0.1, 0, 0]))  # Adjust the pull parameter as needed\n",
    "fig.update_layout(\n",
    "    title='Number of Tasks',\n",
    "    width=500,\n",
    ")\n",
    "fig.show()"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tổng thời gian log billable: 177.32 h\n",
      "Tổng thời gian log utilized: 380.23 h\n"
     ]
    }
   ],
   "source": [
    "# sum(billable_df[\"Logged\"]), sum(ultilized_df[\"Logged\"])\n",
    "print(f\"Tổng thời gian log billable: {round(sum(billable_df['Logged']),2)} h\")\n",
    "print(f\"Tổng thời gian log utilized: {round(sum(billable_df['Logged']) + sum(ultilized_df['Logged']),2)} h\")"
   ]
  },
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    "hours_data = {\"utilized\": round(sum(billable_df['Logged']) + sum(ultilized_df['Logged']),2)}\n",
    "hours_data[\"non-utilized\"] = round(sum(df[\"Logged\"]) - hours_data[\"utilized\"], 2)\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Bar(x=list(hours_data.keys()), y=list(hours_data.values()), text=list(hours_data.values()), textposition='auto'))\n",
    "fig.update_layout(\n",
    "    title='Hours logged',\n",
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    "    yaxis_title='Hours',\n",
    "    width=500,\n",
    ")\n",
    "fig.show()"
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    "hours_data_pie = {\"billable\": round(sum(billable_df['Logged']),2), \"utilized\": round(sum(ultilized_df['Logged']),2)}\n",
    "hours_data_pie[\"non-utilized\"] = round(sum(df[\"Logged\"]) - hours_data_pie[\"utilized\"] - hours_data_pie[\"billable\"], 2)\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Pie(labels=list(hours_data_pie.keys()), values=list(hours_data_pie.values()),\n",
    "                     textinfo='label+percent', pull=[0.1, 0, 0]))  # Adjust the pull parameter as needed\n",
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    "    title='Hours logged',\n",
    "    width=500,\n",
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    "fig.show()"
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  },
  {
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    "df[\"Project\"] = df[\"Key\"].apply(lambda key: key[:3])\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Bar(x=df[\"Project\"].value_counts().index, y=df[\"Project\"].value_counts().values, text=list(df[\"Project\"].value_counts().values), textposition='outside'))\n",
    "fig.update_layout(\n",
    "    title='Project Distribution',\n",
    "    xaxis_title='Project',\n",
    "    yaxis_title='Hours',\n",
    "    width=800,\n",
    ")\n",
    "fig.show()"
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  },
  {
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    "                     textinfo='label+percent', pull=[0.1, 0, 0]))  # Adjust the pull parameter as needed\n",
    "fig.update_layout(title='Project Distribution', width=800)\n",
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    "for proj in df[\"Project\"].value_counts().index:\n",
    "    proj_df = df[df[\"Key\"].apply(lambda x: x.startswith(proj))]\n",
    "    project_hours_data.append((proj, round(sum(proj_df[\"Logged\"]), 2)))"
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    "# billable_df[billable_df[\"Logged\"].apply(lambda x: x > 5)][[\"Key\", \"Logged\"]]\n",
    "filtered_df = billable_df[billable_df[\"Logged\"].apply(lambda x: x > 5)][[\"Key\", \"Logged\"]]\n",
    "\n",
    "fig = px.bar(\n",
    "    filtered_df,\n",
    "    x=\"Key\",\n",
    "    y=\"Logged\",\n",
    "    text=\"Logged\",\n",
    "    title=\"Billable tasks with more than 5 hours logged\",\n",
    "    labels={\"Logged\": \"Logged Hours\", \"Key\": \"Task\"},\n",
    "    height=500,\n",
    ")\n",
    "fig.update_traces(textposition='outside')\n",
    "fig.update_layout(\n",
    "    xaxis=dict(tickangle=45, tickmode='linear'),\n",
    "    yaxis_title=\"Logged Hours\",\n",
    "    xaxis_title=\"Key\",\n",
    ")\n",
    "fig.show()"
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   "source": [
    "# billable_df[billable_df[\"Logged\"].apply(lambda x: x > 5)][[\"Key\", \"Logged\"]]\n",
    "filtered_df = billable_df[billable_df[\"Logged\"].apply(lambda x: x < 1)][[\"Key\", \"Logged\"]]\n",
    "\n",
    "fig = px.bar(\n",
    "    filtered_df,\n",
    "    x=\"Key\",\n",
    "    y=\"Logged\",\n",
    "    text=\"Logged\",\n",
    "    title=\"Billable tasks less than 1 hour logged\",\n",
    "    labels={\"Logged\": \"Logged Hours\", \"Key\": \"Task\"},\n",
    "    height=500,\n",
    ")\n",
    "fig.update_traces(textposition='outside')\n",
    "fig.update_layout(\n",
    "    xaxis=dict(tickangle=45, tickmode='linear'),\n",
    "    yaxis_title=\"Logged Hours\",\n",
    "    xaxis_title=\"Key\",\n",
    ")\n",
    "fig.show()"
   ]
  },
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    "# ultilized_df[ultilized_df[\"Logged\"].apply(lambda x: x > 5)][[\"Key\", \"Logged\"]]\n",
    "filtered_df = ultilized_df[ultilized_df[\"Logged\"].apply(lambda x: x > 5)][[\"Key\", \"Logged\"]]\n",
    "\n",
    "fig = px.bar(\n",
    "    filtered_df,\n",
    "    x=\"Key\",\n",
    "    y=\"Logged\",\n",
    "    text=\"Logged\",\n",
    "    title=\"Utilized tasks with more than 5 hours logged\",\n",
    "    labels={\"Logged\": \"Logged Hours\", \"Key\": \"Task\"},\n",
    "    height=500,\n",
    ")\n",
    "fig.update_traces(textposition='outside')\n",
    "fig.update_layout(\n",
    "    xaxis=dict(tickangle=45, tickmode='linear'),\n",
    "    yaxis_title=\"Logged Hours\",\n",
    "    xaxis_title=\"Key\",\n",
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    "fig.show()"
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    "filtered_df = ultilized_df[ultilized_df[\"Logged\"].apply(lambda x: x < 1)][[\"Key\", \"Logged\"]]\n",
    "\n",
    "fig = px.bar(\n",
    "    filtered_df,\n",
    "    x=\"Key\",\n",
    "    y=\"Logged\",\n",
    "    text=\"Logged\",\n",
    "    title=\"Billable tasks less than 1 hour logged\",\n",
    "    labels={\"Logged\": \"Logged Hours\", \"Key\": \"Task\"},\n",
    "    height=500,\n",
    ")\n",
    "fig.update_traces(textposition='outside')\n",
    "fig.update_layout(\n",
    "    xaxis=dict(tickangle=45, tickmode='linear'),\n",
    "    yaxis_title=\"Logged Hours\",\n",
    "    xaxis_title=\"Key\",\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
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   "source": [
    "date_columns = [date for date in df.columns if date not in [\"Issue\", \"Key\", \"Logged\", \"Project\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Số ngày làm việc hơn 8 tiếng: 26 ngày\n"
     ]
    }
   ],
   "source": [
    "work_data = []\n",
    "for col in date_columns:\n",
    "    if sum(df[col]) > 8:\n",
    "        work_data.append((col, sum(df[col])))\n",
    "print(f\"Số ngày làm việc hơn 8 tiếng: {len(work_data)} ngày\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Số ngày nghỉ: 29 ngày\n"
     ]
    }
   ],
   "source": [
    "no_work_data = []\n",
    "for col in date_columns:\n",
    "    if sum(df[col]) < 8:\n",
    "        no_work_data.append((col, sum(df[col])))\n",
    "print(f\"Số ngày nghỉ: {len(no_work_data)} ngày\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tổng số ngày đi làm: 67\n",
      "Tỉ lệ số ngày làm hơn 8 tiếng: 38.81%\n"
     ]
    }
   ],
   "source": [
    "work_days = len(date_columns) - len(no_work_data)\n",
    "print(f\"Tổng số ngày đi làm: {work_days}\")\n",
    "print(f\"Tỉ lệ số ngày làm hơn 8 tiếng: {round((len(work_data) / work_days) * 100, 2)}%\")"
   ]
  },
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           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
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          },
          "title": {
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          "xaxis": {
           "automargin": true,
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           "ticks": "",
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          "yaxis": {
           "automargin": true,
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        },
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         "title": {
          "text": "Date"
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        "yaxis": {
         "title": {
          "text": "Value"
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      }
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "dates, values = zip(*work_data)\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Bar(x=dates, y=values, text=values, textposition='outside'))\n",
    "fig.update_layout(\n",
    "    title='Days with more than 8 hours logged',\n",
    "    xaxis_title='Date',\n",
    "    yaxis_title='Value',\n",
    ")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trung bình log 1 ngày: 8.20865671641791\n"
     ]
    }
   ],
   "source": [
    "print(f\"Trung bình log 1 ngày: {sum(df['Logged']) / work_days}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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