Minor restructuring of Lesson 1.2.1

Author: turukawa

Lesson 1-2-1 - Introduction to Jupyter Notebook and programming in Python.ipynb

@@ -2077,343 +2077,7 @@
    "source": [
     "Using `*args` and `**kwargs` in your function calls while you're developing makes it easier to change your code without having to go back through every line of code that calls your function and bug-fix when you change the order or number of arguments you're calling. \n",
     "\n",
-    "This reduces errors, improves readability, and makes for a more enjoyable and efficient coding experience.\n",
-    "\n",
-    "At this stage, you've learned the fundamental syntax, as well as how to create modular code. There is a great deal more to learn, but we will cover only one more thing before heading back into data wrangling."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Built-in modules\n",
-    "\n",
-    "There are a vast range of built-in modules. Jupyter Notebook comes with an even larger list of third-party modules you can explore.\n",
-    "\n",
-    "<div class=\"alert alert-block alert-info\">\n",
-    "    <b>Syntax</b>\n",
-    "    <br>\n",
-    "    <ul>\n",
-    "        <li>After you've imported a module, <code>dir(module)</code> lets you see a list of all the functions implemented in that library.</li>\n",
-    "        <li>You can also read the help from the module docstrings with <code>help(module)</code></li>\n",
-    "    </ul>\n",
-    "</div>\n",
-    "\n",
-    "Let's explore a module you'll be using and learning about in future sessions of this course, `pandas`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Help on package pandas:\n",
-      "\n",
-      "NAME\n",
-      "    pandas\n",
-      "\n",
-      "DESCRIPTION\n",
-      "    pandas - a powerful data analysis and manipulation library for Python\n",
-      "    =====================================================================\n",
-      "    \n",
-      "    **pandas** is a Python package providing fast, flexible, and expressive data\n",
-      "    structures designed to make working with \"relational\" or \"labeled\" data both\n",
-      "    easy and intuitive. It aims to be the fundamental high-level building block for\n",
-      "    doing practical, **real world** data analysis in Python. Additionally, it has\n",
-      "    the broader goal of becoming **the most powerful and flexible open source data\n",
-      "    analysis / manipulation tool available in any language**. It is already well on\n",
-      "    its way toward this goal.\n",
-      "    \n",
-      "    Main Features\n",
-      "    -------------\n",
-      "    Here are just a few of the things that pandas does well:\n",
-      "    \n",
-      "      - Easy handling of missing data in floating point as well as non-floating\n",
-      "        point data\n",
-      "      - Size mutability: columns can be inserted and deleted from DataFrame and\n",
-      "        higher dimensional objects\n",
-      "      - Automatic and explicit data alignment: objects can  be explicitly aligned\n",
-      "        to a set of labels, or the user can simply ignore the labels and let\n",
-      "        `Series`, `DataFrame`, etc. automatically align the data for you in\n",
-      "        computations\n",
-      "      - Powerful, flexible group by functionality to perform split-apply-combine\n",
-      "        operations on data sets, for both aggregating and transforming data\n",
-      "      - Make it easy to convert ragged, differently-indexed data in other Python\n",
-      "        and NumPy data structures into DataFrame objects\n",
-      "      - Intelligent label-based slicing, fancy indexing, and subsetting of large\n",
-      "        data sets\n",
-      "      - Intuitive merging and joining data sets\n",
-      "      - Flexible reshaping and pivoting of data sets\n",
-      "      - Hierarchical labeling of axes (possible to have multiple labels per tick)\n",
-      "      - Robust IO tools for loading data from flat files (CSV and delimited),\n",
-      "        Excel files, databases, and saving/loading data from the ultrafast HDF5\n",
-      "        format\n",
-      "      - Time series-specific functionality: date range generation and frequency\n",
-      "        conversion, moving window statistics, moving window linear regressions,\n",
-      "        date shifting and lagging, etc.\n",
-      "\n",
-      "PACKAGE CONTENTS\n",
-      "    _libs (package)\n",
-      "    _version\n",
-      "    api (package)\n",
-      "    compat (package)\n",
-      "    computation (package)\n",
-      "    conftest\n",
-      "    core (package)\n",
-      "    errors (package)\n",
-      "    formats (package)\n",
-      "    io (package)\n",
-      "    json\n",
-      "    lib\n",
-      "    parser\n",
-      "    plotting (package)\n",
-      "    stats (package)\n",
-      "    testing\n",
-      "    tests (package)\n",
-      "    tools (package)\n",
-      "    tseries (package)\n",
-      "    tslib\n",
-      "    types (package)\n",
-      "    util (package)\n",
-      "\n",
-      "SUBMODULES\n",
-      "    _hashtable\n",
-      "    _lib\n",
-      "    _tslib\n",
-      "    offsets\n",
-      "\n",
-      "DATA\n",
-      "    IndexSlice = <pandas.core.indexing._IndexSlice object>\n",
-      "    NaT = NaT\n",
-      "    __docformat__ = 'restructuredtext'\n",
-      "    datetools = <module 'pandas.core.datetools' from 'C:\\\\Users\\...\\lib\\\\s...\n",
-      "    describe_option = <pandas.core.config.CallableDynamicDoc object>\n",
-      "    get_option = <pandas.core.config.CallableDynamicDoc object>\n",
-      "    json = <module 'pandas.json' from 'C:\\\\Users\\\\Turukawa\\...atascience\\\\...\n",
-      "    lib = <module 'pandas.lib' from 'C:\\\\Users\\\\Turukawa\\\\...datascience\\\\...\n",
-      "    options = <pandas.core.config.DictWrapper object>\n",
-      "    parser = <module 'pandas.parser' from 'C:\\\\Users\\\\Turukaw...ascience\\\\...\n",
-      "    plot_params = {'xaxis.compat': False}\n",
-      "    reset_option = <pandas.core.config.CallableDynamicDoc object>\n",
-      "    set_option = <pandas.core.config.CallableDynamicDoc object>\n",
-      "    tslib = <module 'pandas.tslib' from 'C:\\\\Users\\\\Turukawa...tascience\\\\...\n",
-      "\n",
-      "VERSION\n",
-      "    0.21.1\n",
-      "\n",
-      "FILE\n",
-      "    c:\\users\\turukawa\\anaconda3\\envs\\datascience\\lib\\site-packages\\pandas\\__init__.py\n",
-      "\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "\n",
-    "help(pd)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['Categorical',\n",
-       " 'CategoricalIndex',\n",
-       " 'DataFrame',\n",
-       " 'DateOffset',\n",
-       " 'DatetimeIndex',\n",
-       " 'ExcelFile',\n",
-       " 'ExcelWriter',\n",
-       " 'Expr',\n",
-       " 'Float64Index',\n",
-       " 'Grouper',\n",
-       " 'HDFStore',\n",
-       " 'Index',\n",
-       " 'IndexSlice',\n",
-       " 'Int64Index',\n",
-       " 'Interval',\n",
-       " 'IntervalIndex',\n",
-       " 'MultiIndex',\n",
-       " 'NaT',\n",
-       " 'Panel',\n",
-       " 'Panel4D',\n",
-       " 'Period',\n",
-       " 'PeriodIndex',\n",
-       " 'RangeIndex',\n",
-       " 'Series',\n",
-       " 'SparseArray',\n",
-       " 'SparseDataFrame',\n",
-       " 'SparseList',\n",
-       " 'SparseSeries',\n",
-       " 'Term',\n",
-       " 'TimeGrouper',\n",
-       " 'Timedelta',\n",
-       " 'TimedeltaIndex',\n",
-       " 'Timestamp',\n",
-       " 'UInt64Index',\n",
-       " 'WidePanel',\n",
-       " '_DeprecatedModule',\n",
-       " '__builtins__',\n",
-       " '__cached__',\n",
-       " '__doc__',\n",
-       " '__docformat__',\n",
-       " '__file__',\n",
-       " '__loader__',\n",
-       " '__name__',\n",
-       " '__package__',\n",
-       " '__path__',\n",
-       " '__spec__',\n",
-       " '__version__',\n",
-       " '_hashtable',\n",
-       " '_lib',\n",
-       " '_libs',\n",
-       " '_np_version_under1p10',\n",
-       " '_np_version_under1p11',\n",
-       " '_np_version_under1p12',\n",
-       " '_np_version_under1p13',\n",
-       " '_np_version_under1p14',\n",
-       " '_np_version_under1p15',\n",
-       " '_tslib',\n",
-       " '_version',\n",
-       " 'api',\n",
-       " 'bdate_range',\n",
-       " 'compat',\n",
-       " 'concat',\n",
-       " 'core',\n",
-       " 'crosstab',\n",
-       " 'cut',\n",
-       " 'date_range',\n",
-       " 'datetime',\n",
-       " 'datetools',\n",
-       " 'describe_option',\n",
-       " 'errors',\n",
-       " 'eval',\n",
-       " 'ewma',\n",
-       " 'ewmcorr',\n",
-       " 'ewmcov',\n",
-       " 'ewmstd',\n",
-       " 'ewmvar',\n",
-       " 'ewmvol',\n",
-       " 'expanding_apply',\n",
-       " 'expanding_corr',\n",
-       " 'expanding_count',\n",
-       " 'expanding_cov',\n",
-       " 'expanding_kurt',\n",
-       " 'expanding_max',\n",
-       " 'expanding_mean',\n",
-       " 'expanding_median',\n",
-       " 'expanding_min',\n",
-       " 'expanding_quantile',\n",
-       " 'expanding_skew',\n",
-       " 'expanding_std',\n",
-       " 'expanding_sum',\n",
-       " 'expanding_var',\n",
-       " 'factorize',\n",
-       " 'get_dummies',\n",
-       " 'get_option',\n",
-       " 'get_store',\n",
-       " 'groupby',\n",
-       " 'infer_freq',\n",
-       " 'interval_range',\n",
-       " 'io',\n",
-       " 'isna',\n",
-       " 'isnull',\n",
-       " 'json',\n",
-       " 'lib',\n",
-       " 'lreshape',\n",
-       " 'match',\n",
-       " 'melt',\n",
-       " 'merge',\n",
-       " 'merge_asof',\n",
-       " 'merge_ordered',\n",
-       " 'notna',\n",
-       " 'notnull',\n",
-       " 'np',\n",
-       " 'offsets',\n",
-       " 'option_context',\n",
-       " 'options',\n",
-       " 'ordered_merge',\n",
-       " 'pandas',\n",
-       " 'parser',\n",
-       " 'period_range',\n",
-       " 'pivot',\n",
-       " 'pivot_table',\n",
-       " 'plot_params',\n",
-       " 'plotting',\n",
-       " 'pnow',\n",
-       " 'qcut',\n",
-       " 'read_clipboard',\n",
-       " 'read_csv',\n",
-       " 'read_excel',\n",
-       " 'read_feather',\n",
-       " 'read_fwf',\n",
-       " 'read_gbq',\n",
-       " 'read_hdf',\n",
-       " 'read_html',\n",
-       " 'read_json',\n",
-       " 'read_msgpack',\n",
-       " 'read_parquet',\n",
-       " 'read_pickle',\n",
-       " 'read_sas',\n",
-       " 'read_sql',\n",
-       " 'read_sql_query',\n",
-       " 'read_sql_table',\n",
-       " 'read_stata',\n",
-       " 'read_table',\n",
-       " 'reset_option',\n",
-       " 'rolling_apply',\n",
-       " 'rolling_corr',\n",
-       " 'rolling_count',\n",
-       " 'rolling_cov',\n",
-       " 'rolling_kurt',\n",
-       " 'rolling_max',\n",
-       " 'rolling_mean',\n",
-       " 'rolling_median',\n",
-       " 'rolling_min',\n",
-       " 'rolling_quantile',\n",
-       " 'rolling_skew',\n",
-       " 'rolling_std',\n",
-       " 'rolling_sum',\n",
-       " 'rolling_var',\n",
-       " 'rolling_window',\n",
-       " 'scatter_matrix',\n",
-       " 'set_eng_float_format',\n",
-       " 'set_option',\n",
-       " 'show_versions',\n",
-       " 'stats',\n",
-       " 'test',\n",
-       " 'testing',\n",
-       " 'timedelta_range',\n",
-       " 'to_datetime',\n",
-       " 'to_msgpack',\n",
-       " 'to_numeric',\n",
-       " 'to_pickle',\n",
-       " 'to_timedelta',\n",
-       " 'tools',\n",
-       " 'tseries',\n",
-       " 'tslib',\n",
-       " 'unique',\n",
-       " 'util',\n",
-       " 'value_counts',\n",
-       " 'wide_to_long']"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "dir(pd)"
+    "This reduces errors, improves readability, and makes for a more enjoyable and efficient coding experience."
    ]
   },
   {
@@ -2442,7 +2106,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.7.7"
   }
  },
  "nbformat": 4,