* **Aware times and datetimes have defined timezone, while naive don't. If object is naive, it is presumed to be in the system's timezone!**
* **Times and datetimes that have defined timezone are called aware and ones that don't, naive. If object is naive, it is presumed to be in the system's timezone!**
* **`'fold=1'` means the second pass in case of time jumping back for one hour.**
* **Timedelta normalizes arguments to ±days, seconds (<86400)andmicroseconds(<1M).Itsstr()methodreturns`'[±D, ]H:MM:SS[.…]'`andtotal_seconds()afloatofallseconds.**
* **Use `'<D/DT>.weekday()'` to get the day of the week as an int, with Monday being 0.**
@ -1155,7 +1155,8 @@ class MySortable:
### Iterator
* **Any object that has methods next() and iter() is an iterator.**
* **Next() should return next item or raise StopIteration exception.**
* **Iter() should return 'self', i.e. unmodified object on which it was called.**
* **Iter() should return an iterator of remaining items, i.e. 'self'.**
* **Only objects that have iter() method can be used in for loops.**
```python
class Counter:
def __init__(self):
@ -1181,7 +1182,7 @@ class Counter:
### Callable
* **All functions and classes have a call() method, hence are callable.**
* **Use `'callable(<obj>)'` or `'isinstance(<obj>, collections.abc.Callable)'` to check if object is callable. Calling an uncallable object raises `'TypeError'`.**
* **Use `'callable(<obj>)'` or `'isinstance(<obj>, collections.abc.Callable)'` to check if object is callable. Calling an uncallable object raises TypeError.**
* **When this cheatsheet uses `'<function>'` as an argument, it means `'<callable>'`.**
```python
class Counter:
@ -1727,8 +1728,8 @@ os.remove(<path>) # Deletes the file.
os.rmdir(<path>) # Deletes the empty directory.
shutil.rmtree(<path>) # Deletes the directory.
```
* **Paths can be either strings, Paths, or DirEntry objects.**
* **Functions report OS related errors by raising either OSError or one of its [subclasses](#exceptions-1).**
* **Paths can be either strings, Path objects, or DirEntry objects.**
* **Functions report OS related errors by raising OSError or one of its [subclasses](#exceptions-1).**
### Shell Commands
```python
@ -2257,7 +2258,7 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
<Thread>.join() # Waits for the thread to finish executing.
```
* **Use `'kwargs=<dict>'` to pass keyword arguments to the function.**
* **Use `'daemon=True'`, or the program will not be able to exit while the thread is alive.**
* **Use `'daemon=True'`, or program won't be able to exit while the thread is alive.**
### Lock
```python
@ -3185,9 +3186,10 @@ Name: a, dtype: int64
<S>.plot.line/area/bar/pie/hist() # Generates a plot. `plt.show()` displays it.
```
* **Use `'print(<S>.to_string())'` to print a Series that has more than 60 items.**
* **Indexing objects can't be tuples because `'obj[x, y]'` is converted to `'obj[(x, y)]'`.**
* **Use `'<S>.index'` to get collection of keys and `'<S>.index = <coll>'` to update them.**
* **Only pass a list or Series to loc/iloc because `'obj[x, y]'` is converted to `'obj[(x, y)]'` and `'<S>.loc[key_1, key_2]'` is how you retrieve a value from a multi-indexed Series.**
* **Pandas uses NumPy types like `'np.int64'`. Series is converted to `'float64'` if we assign np.nan to any item. Use `'<S>.astype(<str/type>)'` to get converted Series.**
* **Series will silently overflow if we run `'pd.Series([100], dtype="int8") + 100'`!**
* **Series will silently overflow if you run `'pd.Series([100], dtype="int8") + 100'`!**
<li><strong>Aware times and datetimes have defined timezone, while naive don't. If object is naive, it is presumed to be in the system's timezone!</strong></li>
<li><strong>Times and datetimes that have defined timezone are called aware and ones that don't, naive. If object is naive, it is presumed to be in the system's timezone!</strong></li>
<li><strong><codeclass="python hljs"><spanclass="hljs-string">'fold=1'</span></code> means the second pass in case of time jumping back for one hour.</strong></li>
<li><strong>Timedelta normalizes arguments to ±days, seconds (< 86 400) and microseconds (< 1M). Its str() method returns <codeclass="python hljs"><spanclass="hljs-string">'[±D, ]H:MM:SS[.…]'</span></code> and total_seconds() a float of all seconds.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'<D/DT>.weekday()'</span></code> to get the day of the week as an int, with Monday being 0.</strong></li>
@ -988,7 +988,8 @@ P = make_dataclass(<span class="hljs-string">'P'</span>, [(<span class="hljs-str
<div><h3id="iterator-1">Iterator</h3><ul>
<li><strong>Any object that has methods next() and iter() is an iterator.</strong></li>
<li><strong>Next() should return next item or raise StopIteration exception.</strong></li>
<li><strong>Iter() should return 'self', i.e. unmodified object on which it was called.</strong></li>
<li><strong>Iter() should return an iterator of remaining items, i.e. 'self'.</strong></li>
<li><strong>Only objects that have iter() method can be used in for loops.</strong></li>
@ -1011,7 +1012,7 @@ P = make_dataclass(<span class="hljs-string">'P'</span>, [(<span class="hljs-str
<li><strong>File objects returned by the <ahref="#open">open()</a> function, etc.</strong></li>
</ul><div><h3id="callable">Callable</h3><ul>
<li><strong>All functions and classes have a call() method, hence are callable.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'callable(<obj>)'</span></code> or <codeclass="python hljs"><spanclass="hljs-string">'isinstance(<obj>, collections.abc.Callable)'</span></code> to check if object is callable. Calling an uncallable object raises <codeclass="python hljs"><spanclass="hljs-string">'TypeError'</span></code>.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'callable(<obj>)'</span></code> or <codeclass="python hljs"><spanclass="hljs-string">'isinstance(<obj>, collections.abc.Callable)'</span></code> to check if object is callable. Calling an uncallable object raises TypeError.</strong></li>
<li><strong>When this cheatsheet uses <codeclass="python hljs"><spanclass="hljs-string">'<function>'</span></code> as an argument, it means <codeclass="python hljs"><spanclass="hljs-string">'<callable>'</span></code>.</strong></li>
<str> = <pipe>.read(size=<spanclass="hljs-number">-1</span>) <spanclass="hljs-comment"># Reads 'size' chars or until EOF. Also readline/s().</span>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'kwargs=<dict>'</span></code> to pass keyword arguments to the function.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'daemon=True'</span></code>, or the program will not be able to exit while the thread is alive.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'daemon=True'</span></code>, or program won't be able to exit while the thread is alive.</strong></li>
</ul>
<div><h3id="lock">Lock</h3><pre><codeclass="python language-python hljs"><lock> = Lock/RLock() <spanclass="hljs-comment"># RLock can only be released by acquirer.</span>
<lock>.acquire() <spanclass="hljs-comment"># Waits for the lock to be available.</span>
@ -2612,9 +2613,10 @@ Name: a, dtype: int64
</code></pre>
<ul>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'print(<S>.to_string())'</span></code> to print a Series that has more than 60 items.</strong></li>
<li><strong>Indexing objects can't be tuples because <codeclass="python hljs"><spanclass="hljs-string">'obj[x, y]'</span></code> is converted to <codeclass="python hljs"><spanclass="hljs-string">'obj[(x, y)]'</span></code>.</strong></li>
<li><strong>Use <codeclass="python hljs"><spanclass="hljs-string">'<S>.index'</span></code> to get collection of keys and <codeclass="python hljs"><spanclass="hljs-string">'<S>.index = <coll>'</span></code> to update them.</strong></li>
<li><strong>Only pass a list or Series to loc/iloc because <codeclass="python hljs"><spanclass="hljs-string">'obj[x, y]'</span></code> is converted to <codeclass="python hljs"><spanclass="hljs-string">'obj[(x, y)]'</span></code> and <codeclass="python hljs"><spanclass="hljs-string">'<S>.loc[key_1, key_2]'</span></code> is how you retrieve a value from a multi-indexed Series.</strong></li>
<li><strong>Pandas uses NumPy types like <codeclass="python hljs"><spanclass="hljs-string">'np.int64'</span></code>. Series is converted to <codeclass="python hljs"><spanclass="hljs-string">'float64'</span></code> if we assign np.nan to any item. Use <codeclass="python hljs"><spanclass="hljs-string">'<S>.astype(<str/type>)'</span></code> to get converted Series.</strong></li>
<li><strong>Series will silently overflow if we run <codeclass="python hljs"><spanclass="hljs-string">'pd.Series([100], dtype="int8") + 100'</span></code>!</strong></li>
<li><strong>Series will silently overflow if you run <codeclass="python hljs"><spanclass="hljs-string">'pd.Series([100], dtype="int8") + 100'</span></code>!</strong></li>
<li><strong>Last result has a multi-index. Use <codeclass="python hljs"><spanclass="hljs-string">'<S>[key_1, key_2]'</span></code> to get its values.</strong></li>
</ul>
<div><h3id="dataframe">DataFrame</h3><p><strong>Table with labeled rows and columns.</strong></p><pre><codeclass="python language-python hljs"><spanclass="hljs-meta">>>></span>df = pd.DataFrame([[<spanclass="hljs-number">1</span>, <spanclass="hljs-number">2</span>], [<spanclass="hljs-number">3</span>, <spanclass="hljs-number">4</span>]], index=[<spanclass="hljs-string">'a'</span>, <spanclass="hljs-string">'b'</span>], columns=[<spanclass="hljs-string">'x'</span>, <spanclass="hljs-string">'y'</span>]); df
x y
a <spanclass="hljs-number">1</span><spanclass="hljs-number">2</span>
@ -2942,7 +2941,7 @@ $ deactivate <span class="hljs-comment"># Deactivates the active
Jure Šorn
1 week ago