<jupyter_start><jupyter_text>Lesson 1Two goals:1. Get familiar with Jupyter1. Different types of values (data)We are going to cover 4 data types: * integer* decimal (called "float")* strings (for letters)* true/false (called Boolean) Step 1Enter some math expression in a Jupyter cell. Press Control+Enter to for it to calculate. Or use the Play button by the menu.For example```python1+12```<jupyter_code>1+1
24*3<jupyter_output><empty_output><jupyter_text>Try some of your own.To create a new cell, use the "+" button by the menu, or use Esc-B.  Step 2Now try this for division```python1//2```Did you get what you expected?<jupyter_code>1//2<jupyter_output><empty_output><jupyter_text>Computer languages treat integers and decimals as different types.You can "ask" Python what the data type is.```Pythontype(1)type(1.0)```You'll see that "decimal" numbers are called  "float". (The reason for that term is technical....)<jupyter_code>type(1)
type(1.0)<jupyter_output><empty_output><jupyter_text>Now try```Python1.0/2.0```and ```Python1/2```* In the first case we divide two floats.* In the second, a single / means to do "floating division"  * A double // means do "integer division"  Other data typesBesides integer and float there are StringsShort for "string of letters"```Python'abcdef'type('abcdef')```<jupyter_code>type('abcdef')<jupyter_output><empty_output><jupyter_text>What happens if you add two strings?```Python'Hello'+'World'```<jupyter_code>'Hello'+'World'<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.12508316699933467, 'fraction_numerical': 0.01996007984031936, 'mean_word_length': 6.595959595959596, 'pattern_counts': {'":': 0, '<': 21, '<?xml version=': 0, '>': 21, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '157970', 'license': 'MIT', 'n_tokens_mistral': 515, 'n_tokens_neox': 481, 'n_words': 159, 'path': 'Lesson 1.ipynb', 'repo_name': 'ajlindeman/PyBear', 'size': '1503'}