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39 | 39 | "cell_type": "markdown",
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40 | 40 | "source": [
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41 | 41 | "\n",
|
42 |
| - "1. 📚 Introduction\n", |
43 |
| - "2. 📚 Array Creation\n", |
44 |
| - "3. 📚 Arthimetic Operations\n", |
45 |
| - "4. 📚 Basic Mathematic Operations\n", |
46 |
| - "5. 📚 Statistical Analysis\n", |
47 |
| - "6. 📚 Linear Algebra\n", |
48 |
| - "7. 📚 Data Cleaning\n", |
| 42 | + "1. 📚 *_[Introduction](#introduction)_*\n", |
| 43 | + "2. 📚 *_[Array Creation](#array_creation)_*\n", |
| 44 | + "3. 📚 *_[Arthimetic Operations](#arthimetic_operations)_*\n", |
| 45 | + "4. 📚 *_[Basic Mathematic Operations](#basic_mathematic_operations)_*\n", |
| 46 | + "5. 📚 *_[Statistical Analysis](#statistical_analysis)_*\n", |
| 47 | + "6. 📚 *_[Linear Algebra](#linear_algebra)_*\n", |
| 48 | + "7. 📚 *_[Data Cleaning](#data_cleaning)_*\n", |
49 | 49 | "\n"
|
50 | 50 | ],
|
51 | 51 | "metadata": {
|
|
55 | 55 | {
|
56 | 56 | "cell_type": "markdown",
|
57 | 57 | "source": [
|
58 |
| - "# **Section 1- Introduction**" |
| 58 | + "# **Section 1- Introduction<a name='introduction'></a>**" |
59 | 59 | ],
|
60 | 60 | "metadata": {
|
61 | 61 | "id": "AvgSpC5aLpUB"
|
|
1087 | 1087 | {
|
1088 | 1088 | "cell_type": "markdown",
|
1089 | 1089 | "source": [
|
1090 |
| - "#**📚Section 2-Array Creation**\n", |
| 1090 | + "#**📚Section 2-Array Creation<a name='array_creation'></a>**\n", |
1091 | 1091 | "\n",
|
1092 | 1092 | "NumPy stands for ‘Numerical Python’. It is an open-source Python library used to perform various mathematical and scientific tasks.NumPy is one of the very first libraries in Python that makes your numerical computations easy and efficient. This course will get you acquainted (familiarize) with NumPy. It contains multi-dimensional arrays and matrices, along with many high-level [link text](https://)"
|
1093 | 1093 | ],
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1593 | 1593 | },
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1594 |
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1646 | 1646 | },
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1647 |
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1682 |
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1714 | 1714 | "id": "Y0D_IzMr3U_L",
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1717 |
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1750 |
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1782 | 1782 | },
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1783 |
| - "execution_count": 11, |
| 1783 | + "execution_count": null, |
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1815 | 1815 | "id": "YHsIhtbl36fV",
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1817 | 1817 | },
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1818 |
| - "execution_count": 12, |
| 1818 | + "execution_count": null, |
1819 | 1819 | "outputs": [
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1820 | 1820 | {
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1821 | 1821 | "output_type": "stream",
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1853 | 1853 | "id": "n5NmgnxGO0Ja",
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1854 | 1854 | "outputId": "8ea4b7ce-398b-4621-d662-2fbff543c728"
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1855 | 1855 | },
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1856 |
| - "execution_count": 2, |
| 1856 | + "execution_count": null, |
1857 | 1857 | "outputs": [
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1858 | 1858 | {
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1859 | 1859 | "output_type": "stream",
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1879 | 1879 | "id": "T5n0rrvdO2ky",
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1880 | 1880 | "outputId": "4b63adac-2239-4e48-d9d2-2a87e139697b"
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1881 | 1881 | },
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1882 |
| - "execution_count": 3, |
| 1882 | + "execution_count": null, |
1883 | 1883 | "outputs": [
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1884 | 1884 | {
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1885 | 1885 | "output_type": "stream",
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1948 | 1948 | {
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1949 | 1949 | "cell_type": "markdown",
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1950 | 1950 | "source": [
|
1951 |
| - "#**📚Section 3- Arthimetic Operations**" |
| 1951 | + "#**📚Section 3- Arthimetic Operations<a name='arthimetic_operations'></a>**" |
1952 | 1952 | ],
|
1953 | 1953 | "metadata": {
|
1954 | 1954 | "id": "3gtbL5POocfK"
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|
2567 | 2567 | "id": "TLMtTQabODat",
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2568 | 2568 | "outputId": "7c55509d-a9a5-4459-968b-27aab5fec21a"
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2569 | 2569 | },
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2570 |
| - "execution_count": 1, |
| 2570 | + "execution_count": null, |
2571 | 2571 | "outputs": [
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2572 | 2572 | {
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2573 | 2573 | "output_type": "stream",
|
|
2624 | 2624 | {
|
2625 | 2625 | "cell_type": "markdown",
|
2626 | 2626 | "source": [
|
2627 |
| - "#**📚Section 4-The Basics operations on Numpy Array**\n", |
| 2627 | + "#**📚Section 4-The Basics operations on Numpy Array<a name='basic_mathematic_operations'></a>**\n", |
2628 | 2628 | "NumPy’s main object is the homogeneous multidimensional array. It is a table of elements (usually numbers), all of the\n",
|
2629 | 2629 | "same type, indexed by a tuple of non-negative integers. In NumPy dimensions are called axes.\n",
|
2630 | 2630 | "For example, the array for the coordinates of a point in 3D space, [1, 2, 1], has one axis. That axis has 3 elements\n",
|
|
3668 | 3668 | "id": "mxdJ-uNE4M80",
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3670 | 3670 | },
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3671 |
| - "execution_count": 14, |
| 3671 | + "execution_count": null, |
3672 | 3672 | "outputs": [
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3673 | 3673 | {
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3674 | 3674 | "output_type": "stream",
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3692 | 3692 | {
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3693 | 3693 | "cell_type": "markdown",
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3694 | 3694 | "source": [
|
3695 |
| - "# **📚Section 5-Statistical Analysis**" |
| 3695 | + "# **📚Section 5-Statistical Analysis<a name='statistical_analysis'></a>**" |
3696 | 3696 | ],
|
3697 | 3697 | "metadata": {
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3698 | 3698 | "id": "5FOpljH3dSOH"
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|
4166 | 4166 | {
|
4167 | 4167 | "cell_type": "markdown",
|
4168 | 4168 | "source": [
|
4169 |
| - "# **📚Section 6 -Linear Algebra**" |
| 4169 | + "# **📚Section 6 -Linear Algebra<a name='linear_algebra'></a>**" |
4170 | 4170 | ],
|
4171 | 4171 | "metadata": {
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4172 | 4172 | "id": "9ac_XaU4Ubv_"
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4194 | 4194 | "metadata": {
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4196 | 4196 | },
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4197 |
| - "execution_count": 5, |
| 4197 | + "execution_count": null, |
4198 | 4198 | "outputs": []
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4199 | 4199 | },
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4200 | 4200 | {
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4222 | 4222 | "metadata": {
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4223 | 4223 | "id": "MV0At4huVuOQ"
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4224 | 4224 | },
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4225 |
| - "execution_count": 7, |
| 4225 | + "execution_count": null, |
4226 | 4226 | "outputs": []
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4227 | 4227 | },
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4228 | 4228 | {
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4427 | 4427 | {
|
4428 | 4428 | "cell_type": "markdown",
|
4429 | 4429 | "source": [
|
4430 |
| - "# **📚Section 7 -Data Cleaning**" |
| 4430 | + "# **📚Section 7 -Data Cleaning<a name='data_cleaning'></a>**" |
4431 | 4431 | ],
|
4432 | 4432 | "metadata": {
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4433 | 4433 | "id": "Ph4nunOxYNLN"
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4458 | 4458 | "base_uri": "https://localhost:8080/"
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4459 | 4459 | }
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4460 | 4460 | },
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4461 |
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| 4461 | + "execution_count": null, |
4462 | 4462 | "outputs": [
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4463 | 4463 | {
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4464 | 4464 | "output_type": "stream",
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