f03a-pandas-series-tworzenie-lekcja.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas - series - tworzenie - lekcja"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tworzenie\n",
    "\n",
    "- Seria `int`\n",
    "- Seria `float`\n",
    "- Seria `str`\n",
    "- Seria `datetime`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://python.astrotech.io/numerical-analysis/numpy/array-dtype.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      1\n",
       "1      2\n",
       "2      3\n",
       "3    127\n",
       "4   -128\n",
       "dtype: int8"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([1, 2, 3, 127, 128], dtype=np.int8)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.1\n",
       "1    2.2\n",
       "2    3.3\n",
       "dtype: float128"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([1.1, 2.2, 3.3], dtype=np.float128)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    a\n",
       "1    b\n",
       "2    c\n",
       "dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series(['a', 'b', 'c'])\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    A\n",
       "1    B\n",
       "2    C\n",
       "3    D\n",
       "4    E\n",
       "5    F\n",
       "6    G\n",
       "7    H\n",
       "8    I\n",
       "9    J\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series(list('ABCDEFGHIJ'))\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     A\n",
       "1     B\n",
       "2     C\n",
       "3     D\n",
       "4     E\n",
       "5     F\n",
       "6     G\n",
       "7     H\n",
       "8     I\n",
       "9     J\n",
       "10    K\n",
       "11    L\n",
       "dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import string\n",
    "\n",
    "s = pd.Series(list(string.ascii_uppercase[:12]))\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2000-01-01\n",
       "1   2000-01-02\n",
       "2   2000-01-03\n",
       "3   2000-01-04\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([\n",
    "    pd.Timestamp('2000-01-01'),\n",
    "    pd.Timestamp('2000-01-02'),\n",
    "    pd.Timestamp('2000-01-03'),\n",
    "    pd.Timestamp('2000-01-04'),    \n",
    "])\n",
    "\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2000-01-01\n",
       "1   2000-01-02\n",
       "2   2000-01-03\n",
       "3   2000-01-04\n",
       "4   2000-01-05\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(pd.date_range('2000-01-01', '2000-01-05'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   2000-01-01\n",
       "1   2000-01-02\n",
       "2   2000-01-03\n",
       "3   2000-01-04\n",
       "dtype: datetime64[ns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([\n",
    "    '2000-01-01',\n",
    "    '2000-01-02',\n",
    "    '2000-01-03',\n",
    "    '2000-01-04',    \n",
    "])\n",
    "\n",
    "s = s.map(pd.Timestamp)\n",
    "s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Atrybuty\n",
    "\n",
    "- Typ danych\n",
    "- Kształt\n",
    "- Ilość wymiarów\n",
    "- Indeks\n",
    "- Wartości"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1.1\n",
       "1    2.2\n",
       "2    3.3\n",
       "dtype: float128"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([1.1, 2.2, 3.3], dtype=np.float128)\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3,)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dtype('float128')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=3, step=1)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.1, 2.2, 3.3], dtype=float128)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Indeksy\n",
    "\n",
    "- Range Index\n",
    "- Numeric Index\n",
    "- String Index\n",
    "- Date Index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=3, step=1)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series([1.1, 2.2, 3.3])\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Float64Index([99.0, 1.1, -101.0], dtype='float64')"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [1.1, 2.2, 3.3]\n",
    "index = [99, 1.1, -101]\n",
    "\n",
    "s = pd.Series(data, index)\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 99.0     1.1\n",
       " 1.1      2.2\n",
       "-101.0    3.3\n",
       "dtype: float64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['a', 'basdasdasds', 'c'], dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [1.1, 2.2, 3.3]\n",
    "index = ['a', 'basdasdasds', 'c']\n",
    "\n",
    "s = pd.Series(data, index)\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a              1.1\n",
       "basdasdasds    2.2\n",
       "c              3.3\n",
       "dtype: float64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [1.1, 2.2, 3.3]\n",
    "index = [pd.Timestamp('2000-01-01'), pd.Timestamp('2000-01-02'), pd.Timestamp('2000-01-03')]\n",
    "\n",
    "s = pd.Series(data, index)\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000-01-01    1.1\n",
       "2000-01-02    2.2\n",
       "2000-01-03    3.3\n",
       "dtype: float64"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'], dtype='datetime64[ns]', freq=None)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [1.1, 2.2, 3.3]\n",
    "index = ['2000-01-01', '2000-01-02', '2000-01-03']\n",
    "index = map(pd.Timestamp, index)\n",
    "# index = [pd.Timestamp(x) for x in index]\n",
    "\n",
    "s = pd.Series(data, index)\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03'], dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = [1.1, 2.2, 3.3]\n",
    "index = pd.date_range('2000-01-01', '2000-01-03', freq='D')\n",
    "\n",
    "\n",
    "s = pd.Series(data, index)\n",
    "s.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000-01-01    1.1\n",
       "2000-01-02    2.2\n",
       "2000-01-03    3.3\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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