10-Reading and Writing Data.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Reading & Writting in Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hi Guys, Welcome to [Tirendaz Academy](https://youtube.com/c/tirendazacademy) 😀\n",
    "</br>\n",
    "In this notebook, I'm going to show data reading & writting in Pandas.\n",
    "</br>\n",
    "Happy Learning 🐱‍🏍 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd  \n",
    "import numpy as np "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_table(\"Data/data.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "    Tom,80,M\n",
       "0   Tim,85,M\n",
       "1   Kim,70,M\n",
       "2  Kate,90,F\n",
       "3  Alex,75,F"
      ]
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     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "df2=pd.read_table(\"Data/data2.txt\")\n",
    "df2"
   ]
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       "    Tom  80  M\n",
       "0   Tim  85  M\n",
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       "3  Alex  75  F"
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    "df2=pd.read_table(\"Data/data2.txt\", sep=\",\")\n",
    "df2"
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       "    Tom  80  M\n",
       "0   Tim  85  M\n",
       "1   Kim  70  M\n",
       "2  Kate  90  F\n",
       "3  Alex  75  F"
      ]
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    "df=pd.read_table(\"Data/data2.txt\", sep=\",\")\n",
    "df"
   ]
  },
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   "execution_count": 6,
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       "      0   1  2\n",
       "0   Tom  80  M\n",
       "1   Tim  85  M\n",
       "2   Kim  70  M\n",
       "3  Kate  90  F\n",
       "4  Alex  75  F"
      ]
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     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "df=pd.read_table(\"Data/data2.txt\",\n",
    "                 sep=\",\",\n",
    "                 header=None)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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      "text/plain": [
       "   name  score sex\n",
       "0   Tom     80   M\n",
       "1   Tim     85   M\n",
       "2   Kim     70   M\n",
       "3  Kate     90   F\n",
       "4  Alex     75   F"
      ]
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    "df=pd.read_table(\"Data/data2.txt\",\n",
    "                 sep=\",\",\n",
    "                 header=None, \n",
    "                 names=[\"name\",\"score\",\"sex\"])\n",
    "df"
   ]
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      "text/plain": [
       "      score sex\n",
       "name           \n",
       "Tom      80   M\n",
       "Tim      85   M\n",
       "Kim      70   M\n",
       "Kate     90   F\n",
       "Alex     75   F"
      ]
     },
     "execution_count": 8,
     "metadata": {},
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    }
   ],
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    "df=pd.read_table(\"Data/data2.txt\",\n",
    "                 sep=\",\",header=None, \n",
    "                 names=[\"name\",\"score\",\"sex\"],\n",
    "                 index_col=\"name\")\n",
    "df"
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   "execution_count": 9,
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       "  lesson  name  one  two\n",
       "0   Math   Kim   80   85\n",
       "1   Math   Tim   90   70\n",
       "2   Math   Tom   70   95\n",
       "3   Stat  Kate   65   90\n",
       "4   Stat  Alex   85   80\n",
       "5   Stat   Sam   55   70"
      ]
     },
     "execution_count": 9,
     "metadata": {},
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    }
   ],
   "source": [
    "df2=pd.read_table(\"Data/data3.txt\",\n",
    "                  sep=\",\")\n",
    "df2"
   ]
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   "cell_type": "code",
   "execution_count": 10,
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       "      <th rowspan=\"3\" valign=\"top\">Stat</th>\n",
       "      <th>Kate</th>\n",
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       "      <th>Alex</th>\n",
       "      <td>85</td>\n",
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       "      <td>70</td>\n",
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      "text/plain": [
       "             one  two\n",
       "lesson name          \n",
       "Math   Kim    80   85\n",
       "       Tim    90   70\n",
       "       Tom    70   95\n",
       "Stat   Kate   65   90\n",
       "       Alex   85   80\n",
       "       Sam    55   70"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2=pd.read_table(\"Data/data3.txt\",\n",
    "                  sep=\",\",\n",
    "                  index_col=[\"lesson\",\"name\"])\n",
    "df2"
   ]
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       "      <th>#hello</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <td>sex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>#scores of students</th>\n",
       "      <th>NaN</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tim</th>\n",
       "      <th>80</th>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kate</th>\n",
       "      <th>85</th>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alex</th>\n",
       "      <th>70</th>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tom</th>\n",
       "      <th>90</th>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kim</th>\n",
       "      <th>75</th>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          #hello\n",
       "name                score    sex\n",
       "#scores of students NaN      NaN\n",
       "Tim                 80         M\n",
       "Kate                85         F\n",
       "Alex                70         M\n",
       "Tom                 90         M\n",
       "Kim                 75         F"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=pd.read_table(\"Data/data4.txt\",sep=\",\")\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>score</th>\n",
       "      <th>sex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tim</td>\n",
       "      <td>80</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kate</td>\n",
       "      <td>85</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alex</td>\n",
       "      <td>70</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tom</td>\n",
       "      <td>90</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kim</td>\n",
       "      <td>75</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   name  score sex\n",
       "0   Tim     80   M\n",
       "1  Kate     85   F\n",
       "2  Alex     70   M\n",
       "3   Tom     90   M\n",
       "4   Kim     75   F"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=pd.read_table(\"Data/data4.txt\",\n",
    "                  sep=\",\", \n",
    "                  skiprows=[0,2])\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>name</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tim</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kate</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alex</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Tom</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kim</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   name  score\n",
       "0   Tim     80\n",
       "1  Kate     85\n",
       "2  Alex     70\n",
       "3   Tom     90\n",
       "4   Kim     75"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=pd.read_table(\"Data/data4.txt\",\n",
    "                  sep=\",\", \n",
    "                  skiprows=[0,2],\n",
    "                  usecols=[0,1])\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "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>name</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tim</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kate</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alex</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   name  score\n",
       "0   Tim     80\n",
       "1  Kate     85\n",
       "2  Alex     70"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3=pd.read_table(\"Data/data4.txt\",\n",
    "                  sep=\",\", \n",
    "                  skiprows=[0,2],\n",
    "                  usecols=[0,1],\n",
    "                  nrows=3)\n",
    "df3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>name</th>\n",
       "      <th>score</th>\n",
       "      <th>sex</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tim</td>\n",
       "      <td>80</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tom</td>\n",
       "      <td>85</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kim</td>\n",
       "      <td>70</td>\n",
       "      <td>F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sam</td>\n",
       "      <td>90</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Efe</td>\n",
       "      <td>75</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  name  score sex\n",
       "0  Tim     80   M\n",
       "1  Tom     85   M\n",
       "2  Kim     70   F\n",
       "3  Sam     90   M\n",
       "4  Efe     75   M"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(\"Data/data.txt\",sep=\"\\t\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"Data/new_data.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Don't forget to follow us on [YouTube](http://youtube.com/tirendazacademy) | [Medium](http://tirendazacademy.medium.com) | [Twitter](http://twitter.com/tirendazacademy) | [GitHub](http://github.com/tirendazacademy) | [Linkedin](https://www.linkedin.com/in/tirendaz-academy) | [Kaggle](https://www.kaggle.com/tirendazacademy) 😎"
   ]
  }
 ],
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