Python_Basics_19(Time and Date with Pandas).ipynb

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          "text": [
            "2022-07-20 04:33:00\n"
          ]
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      "source": [
        "#Time Series Data\n",
        "\n",
        "#Dates and TImes in Pandas\n",
        "\n",
        "#datetime module\n",
        "\n",
        "import datetime\n",
        "\n",
        "df = datetime.datetime(year = 2022, month = 7, day = 20, hour = 4, minute = 33 )\n",
        "print(df)\n",
        "\n",
        "#Note;- Format => YYYY-MM-DD  HR:MIN:SEC"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Printing in string format\n",
        "\n",
        "\n",
        "#strftime() => print time in string format\n",
        "print(df.strftime('%d %B %Y'))"
      ],
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          "text": [
            "20 July 2022\n"
          ]
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      "cell_type": "code",
      "source": [
        "#Format codes:\n",
        "#%Y - full year\n",
        "#%y - last two digits of year\n",
        "#%m - month\n",
        "#%d - day\n",
        "#%H - hour (24 Hr format)\n",
        "#%M - minute\n",
        "#%S - second\n",
        "#%A - full weekday name\n",
        "#%a - abbrevated weekday name\n",
        "#%B - full month name\n",
        "#%b - abbrevated month name"
      ],
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      "execution_count": null,
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      "source": [
        "#Basic usage with Pandas Datetime\n",
        "\n",
        "import pandas as pd\n",
        "\n",
        "d = pd.to_datetime('2022-03-01 21:22:32')\n",
        "print(\"Datetime : \",d)\n",
        "f_date = d.strftime('%Y %B %a')\n",
        "print(\"\\nFormtted datetime : \",f_date)"
      ],
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          "text": [
            "Datetime :  2022-03-01 21:22:32\n",
            "\n",
            "Formtted datetime :  2022 March Tue\n"
          ]
        }
      ]
    },
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      "source": [
        "#Creating  a dataframe  with a Datetime column\n",
        "\n",
        "se = pd.DataFrame({\n",
        "    'Dates' : pd.to_datetime(['2022-03-01','2022-01-01','2022-02-01','2022-03-01','2022-04-01'])\n",
        "})\n",
        "\n",
        "se['Formatted Dates'] = se['Dates'].dt.strftime('%Y %B %A')\n",
        "\n",
        "se\n"
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              "       Dates        Formatted Dates\n",
              "0 2022-03-01     2022 March Tuesday\n",
              "1 2022-01-01  2022 January Saturday\n",
              "2 2022-02-01  2022 February Tuesday\n",
              "3 2022-03-01     2022 March Tuesday\n",
              "4 2022-04-01      2022 April Friday"
            ],
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              "summary": "{\n  \"name\": \"se\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Dates\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2022-01-01 00:00:00\",\n        \"max\": \"2022-04-01 00:00:00\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2022-01-01 00:00:00\",\n          \"2022-04-01 00:00:00\",\n          \"2022-03-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Formatted Dates\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2022 January Saturday\",\n          \"2022 April Friday\",\n          \"2022 March Tuesday\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "#TImestamp\n",
        "\n",
        "ts = pd.Timestamp('2000-03-23')\n",
        "ts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kSuy0e5lcpuQ",
        "outputId": "b2fce2f7-0f7f-42cf-ca1a-336acb27e2b1"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2000-03-23 00:00:00')"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts.month"
      ],
      "metadata": {
        "colab": {
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        },
        "id": "SJZFwqbWdbM5",
        "outputId": "d595024e-46b2-44b4-8fac-d7ef6d28c757"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {},
          "execution_count": 33
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    {
      "cell_type": "code",
      "source": [
        "#Timedelta\n",
        "\n",
        "de = pd.Timedelta(days=2, hours=5)\n",
        "print(de)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jwgjoe1DdTGl",
        "outputId": "b4031056-e2af-4d9a-be74-0daa21d74ecf"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2 days 05:00:00\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ts = pd.Timestamp('2000-03-23')\n",
        "ts + pd.Timedelta('5 days') #adds 5 days to the timestamp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FWhtFNVXd2lx",
        "outputId": "dbacab9c-2100-4226-f9e2-3b64de104299"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('2000-03-28 00:00:00')"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Parsing datatime strings\n",
        "\n",
        "date = pd.to_datetime(\"5th of march, 1997\")\n",
        "date"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DA-p3N_WeLt4",
        "outputId": "ed3f0c84-aa19-4da7-b549-e573b3fd0fac"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Timestamp('1997-03-05 00:00:00')"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ss = pd.Series(['2022-03-01 11:03:23','2022-01-01 11:03:23','2022-02-01 11:03:23',\n",
        "                '2022-03-01 11:03:23','2022-04-01 11:03:23'])\n",
        "s1 = pd.to_datetime(ss,format='%Y-%m-%d %H:%M:%S')\n",
        "print(s1)\n",
        "\n",
        "f_s1 = s1.dt.strftime('%Y %B %A ')\n",
        "f_s1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 345
        },
        "id": "mtjSq5KMfSfB",
        "outputId": "9b5eec45-1d49-4287-a02e-8848d8b77c88"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0   2022-03-01 11:03:23\n",
            "1   2022-01-01 11:03:23\n",
            "2   2022-02-01 11:03:23\n",
            "3   2022-03-01 11:03:23\n",
            "4   2022-04-01 11:03:23\n",
            "dtype: datetime64[ns]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       2022 March Tuesday \n",
              "1    2022 January Saturday \n",
              "2    2022 February Tuesday \n",
              "3       2022 March Tuesday \n",
              "4        2022 April Friday \n",
              "dtype: object"
            ],
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              "      <td>2022 April Friday</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> object</label>"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#fetching specific time\n",
        "\n",
        "s1.dt.hour"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
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        "id": "J5qq07iyhq3a",
        "outputId": "d434851b-a46e-49c6-a7a3-ebe5bc7fc0d0"
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      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    11\n",
              "1    11\n",
              "2    11\n",
              "3    11\n",
              "4    11\n",
              "dtype: int32"
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          },
          "metadata": {},
          "execution_count": 40
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "s1.dt.weekday"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "Cr9phZVXiYNa",
        "outputId": "2ca749b5-3d50-4643-b18d-46dede40db71"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1\n",
              "1    5\n",
              "2    1\n",
              "3    1\n",
              "4    4\n",
              "dtype: int32"
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              "</div><br><label><b>dtype:</b> int32</label>"
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          "metadata": {},
          "execution_count": 41
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#TimeSeries using numpy\n",
        "\n",
        "import numpy as np\n",
        "\n",
        "date + pd.to_timedelta(np.arange(12), 'D')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HWW66uT7imH6",
        "outputId": "279ef8d1-5b30-469e-de41-297c7d08a41c"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['1997-03-05', '1997-03-06', '1997-03-07', '1997-03-08',\n",
              "               '1997-03-09', '1997-03-10', '1997-03-11', '1997-03-12',\n",
              "               '1997-03-13', '1997-03-14', '1997-03-15', '1997-03-16'],\n",
              "              dtype='datetime64[ns]', freq=None)"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Indexing by time\n",
        "\n",
        "index = pd.DatetimeIndex(['1997-03-05', '1997-03-06', '1997-03-07', '1997-03-08',\n",
        "               '1997-03-09', '1997-03-10', '1997-03-11', '1997-03-12',\n",
        "               '1997-03-13', '1997-03-14', '1997-03-15', '1997-03-16'])\n",
        "\n",
        "data = pd.Series(range(12),index = index)\n",
        "data\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 460
        },
        "id": "jc4mDKbyj195",
        "outputId": "dcb6de94-471c-4970-de25-c34a9e074e29"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1997-03-05     0\n",
              "1997-03-06     1\n",
              "1997-03-07     2\n",
              "1997-03-08     3\n",
              "1997-03-09     4\n",
              "1997-03-10     5\n",
              "1997-03-11     6\n",
              "1997-03-12     7\n",
              "1997-03-13     8\n",
              "1997-03-14     9\n",
              "1997-03-15    10\n",
              "1997-03-16    11\n",
              "dtype: int64"
            ],
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              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>1997-03-09</th>\n",
              "      <td>4</td>\n",
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              "      <th>1997-03-10</th>\n",
              "      <td>5</td>\n",
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              "      <th>1997-03-11</th>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997-03-12</th>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997-03-13</th>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997-03-14</th>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997-03-15</th>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997-03-16</th>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 52
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      ]
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      "cell_type": "code",
      "source": [
        "data['1997-03-05' : '1997-03-11']"
      ],
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          "height": 304
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        "id": "H-vdQODmkzpa",
        "outputId": "49741130-d916-40d4-bdc5-61ee0aded095"
      },
      "execution_count": 53,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1997-03-05    0\n",
              "1997-03-06    1\n",
              "1997-03-07    2\n",
              "1997-03-08    3\n",
              "1997-03-09    4\n",
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              "      <th>1997-03-05</th>\n",
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              "      <td>1</td>\n",
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              "      <td>2</td>\n",
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              "      <td>3</td>\n",
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              "    <tr>\n",
              "      <th>1997-03-09</th>\n",
              "      <td>4</td>\n",
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              "      <th>1997-03-10</th>\n",
              "      <td>5</td>\n",
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              "    <tr>\n",
              "      <th>1997-03-11</th>\n",
              "      <td>6</td>\n",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from datetime import datetime\n",
        "dates = pd.to_datetime([datetime(2023,2,1),\"5th of september, 1887\",\n",
        "                       '1997-03-14', '1997-03-15', '1997-03-16'])\n",
        "print(dates)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "l83co_KflieL",
        "outputId": "6d3d9881-e3b2-44cf-ee35-2bc98468052e"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "DatetimeIndex(['2023-02-01', '1887-09-05', '1997-03-14', '1997-03-15',\n",
            "               '1997-03-16'],\n",
            "              dtype='datetime64[ns]', freq=None)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dates.to_period('D')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3ltNrJTKm7mL",
        "outputId": "c0f54332-80ff-4261-a3df-6e083280ac30"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PeriodIndex(['2023-02-01', '1887-09-05', '1997-03-14', '1997-03-15',\n",
              "             '1997-03-16'],\n",
              "            dtype='period[D]')"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Regular Sequences: pd.date_range => generates a sequence of dates between the given range\n",
        "\n",
        "pd.date_range('2023-04-18', '2023-05-1')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7NmNxZV1nqDr",
        "outputId": "2338dcfd-1e24-4308-ef04-b28b6405d5c2"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2023-04-18', '2023-04-19', '2023-04-20', '2023-04-21',\n",
              "               '2023-04-22', '2023-04-23', '2023-04-24', '2023-04-25',\n",
              "               '2023-04-26', '2023-04-27', '2023-04-28', '2023-04-29',\n",
              "               '2023-04-30', '2023-05-01'],\n",
              "              dtype='datetime64[ns]', freq='D')"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.date_range('2023-04-18', periods = 4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DHI5yQoZoPDb",
        "outputId": "31c11ae2-c7b7-4bec-e82f-099b1a10b8e7"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2023-04-18', '2023-04-19', '2023-04-20', '2023-04-21'], dtype='datetime64[ns]', freq='D')"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.date_range('2023-04-18', periods = 4, freq= 'H')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2jFvP_sEo09s",
        "outputId": "593a412c-16c7-445b-a979-c90f52efcc86"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2023-04-18 00:00:00', '2023-04-18 01:00:00',\n",
              "               '2023-04-18 02:00:00', '2023-04-18 03:00:00'],\n",
              "              dtype='datetime64[ns]', freq='H')"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.date_range('2023-04-18', periods = 4, freq= 'M')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c0ZeRP6aphF7",
        "outputId": "936d378c-7626-46e1-f619-38ce48fe4c0f"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatetimeIndex(['2023-04-30', '2023-05-31', '2023-06-30', '2023-07-31'], dtype='datetime64[ns]', freq='M')"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    }
  ]
}