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+# NumPy Cheat Sheet
+
+[NumPy](http://www.numpy.org) is the fundamental package for scientific computing with Python.
+
+### Installation
+If you don't already have it **installed**, you can do so using Pip or Anaconda:
+```
+$ pip install numpy
+```
+or
+```
+$ conda install numpy
+```
+
+This cheat sheet acts as a intro to Python for data science. 
+
+## Index
+1. [Basics](#basics)
+    - [Placeholders](#place)
+    - [Examples](#ex)
+2. [Arrays](#arrays)
+    - [Properties](#props)
+    - [Copying/Sorting](#gops)
+      * [Examples](#array-example)
+    - [Array Manipulation](#man)
+      * [Adding/Removing Elements](#addrem)
+        + [Examples](#array-elements-examples)
+      * [Combining Arrays](#comb)
+        + [Examples](#array-combine-examples)
+      * [Splitting Arrays](#split)
+        + [Examples](#array-split-examples)
+      * [Shaping](#shape)
+      * [Misc](#misc)
+3. [Mathematics](#maths)
+    - [Arithmetic Operations](#ops)
+      * [Examples](#operations-examples)
+    - [Comparison](#comparison)
+      * [Examples](#comparison-example)
+    - [Basic Statistics](#stats)
+      * [Examples](#stats-examples)
+    - [More](#more)
+4. [Slicing and Subsetting](#ss)
+    - [Examples](#exp)
+5. [Tricks](#tricks)
+6. [Credits](#creds)
+
+</br>
+
+## Basics <a name="basics"></a>
+
+One of the most commonly used functions of NumPy are *NumPy arrays*: The essential difference between *lists* and *NumPy arrays* is functionality and speed. *lists* give you basic operation, but *NumPy* adds FFTs, convolutions, fast searching, basic statistics, linear algebra, histograms, etc.</br>
+The most important difference for data science is the ability to do **element-wise calculations** with *NumPy arrays*.
+
+`axis 0` always refers to row </br>
+`axis 1` always refers to column
+
+| Operator     | Description   | Documentation |
+| :------------- | :------------- | :--------|
+|`np.array([1,2,3])`|1d array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html#numpy.array)|
+|`np.array([(1,2,3),(4,5,6)])`|2d array|see above|
+|`np.arange(start,stop,step)`|range array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html)|
+
+### Placeholders <a name="place"></a>
+| Operators | Description |Documentation|
+| :------------- | :------------- |:---------- |
+|`np.linspace(0,2,9)`|Add evenly spaced values btw interval to array of length |[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html)|
+|`np.zeros((1,2))`|Create and array filled with zeros|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros.html)|
+|`np.ones((1,2))`|Creates an array filled with ones|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.ones)|
+|`np.random.random((5,5))`|Creates random array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.random.html)|
+|`np.empty((2,2))`|Creates an empty array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.empty.html)|
+
+### Examples <a name="ex"></a>
+
+```python
+import numpy as np
+
+# 1 dimensional
+x = np.array([1,2,3])
+# 2 dimensional
+y = np.array([(1,2,3),(4,5,6)])
+
+x = np.arange(3)
+>>> array([0, 1, 2])
+
+y = np.arange(3.0)
+>>> array([ 0.,  1.,  2.])
+
+x = np.arange(3,7)
+>>> array([3, 4, 5, 6])
+
+y = np.arange(3,7,2)
+>>> array([3, 5])
+```
+
+</br>
+
+## Array <a name="arrays"></a>
+### Array Properties <a name="props"></a>
+|Syntax|Description|Documentation|
+|:-------------|:-------------|:-----------|
+|`array.shape`|Dimensions (Rows,Columns)|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.shape.html)|
+|`len(array)`|Length of Array|[link](https://docs.python.org/3.5/library/functions.html#len)|
+|`array.ndim`|Number of Array Dimensions|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.ndim.html)|
+|`array.size`|Number of Array Elements|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.size.html)|
+|`array.dtype`|Data Type|[link](https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html)|
+|`array.astype(type)`|Converts to Data Type|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.astype.html)|
+|`type(array)`|Type of Array|[link](https://docs.scipy.org/doc/numpy/user/basics.types.html)|
+
+### Copying/Sorting <a name="gops"></a>
+| Operators | Descriptions     | Documentation |
+| :------------- | :------------- | :----------- |
+|`np.copy(array)`|Creates copy of array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.copy.html)|
+|`other = array.copy()`|Creates deep copy of array|see above|
+|`array.sort()`|Sorts an array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sort.html)|
+|`array.sort(axis=0)`|Sorts axis of array|see above|
+
+#### Examples <a name="array-example"></a>
+```python
+import numpy as np
+# Sort sorts in ascending order
+y = np.array([10, 9, 8, 7, 6, 5, 4, 3, 2, 1])
+y.sort()
+print(y)
+>>> [ 1  2  3  4  5  6  7  8  9  10]
+```
+
+## Array Manipulation Routines <a name="man"></a>
+
+### Adding or Removing Elements <a name="addrem"></a>
+|Operator|Description|Documentation|
+|:-----------|:--------|:---------|
+|`np.append(a,b)`|Append items to array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.append.html)|
+|`np.insert(array, 1, 2, axis)`|Insert items into array at axis 0 or 1|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.insert.html)|
+|`np.resize((2,4))`|Resize array to shape(2,4)|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.resize.html)|
+|`np.delete(array,1,axis)`|Deletes items from array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.delete.html)|
+
+#### Example <a name="array-elements-examples"></a>
+```python
+import numpy as np
+# Append items to array
+a = np.array([(1, 2, 3),(4, 5, 6)])
+b = np.append(a, [(7, 8, 9)])
+print(b)
+>>> [1 2 3 4 5 6 7 8 9]
+
+# Remove index 2 from previous array
+print(np.delete(b, 2))
+>>> [1 2 4 5 6 7 8 9]
+```
+
+### Combining Arrays <a name="comb"></a>
+|Operator|Description|Documentation|
+|:---------|:-------|:---------|
+|`np.concatenate((a,b),axis=0)`|Concatenates 2 arrays, adds to end|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.concatenate.html)|
+|`np.vstack((a,b))`|Stack array row-wise|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.vstack.html)|
+|`np.hstack((a,b))`|Stack array column wise|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.hstack.html#numpy.hstack)|
+
+#### Example <a name="array-combine-examples"></a>
+```python
+import numpy as np
+a = np.array([1, 3, 5])
+b = np.array([2, 4, 6])
+
+# Stack two arrays row-wise
+print(np.vstack((a,b)))
+>>> [[1 3 5]
+     [2 4 6]]
+
+# Stack two arrays column-wise
+print(np.hstack((a,b)))
+>>> [1 3 5 2 4 6]
+```
+
+### Splitting Arrays <a name="split"></a>
+|Operator|Description|Documentation|
+|:---------|:-------|:------|
+|`numpy.split()`||[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.split.html)|
+|`np.array_split(array, 3)`|Split an array in sub-arrays of (nearly) identical size|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.array_split.html#numpy.array_split)|
+|`numpy.hsplit(array, 3)`|Split the array horizontally at 3rd index|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.hsplit.html#numpy.hsplit)|
+
+#### Example <a name="array-split-examples"></a>
+```python
+# Split array into groups of ~3
+a = np.array([1, 2, 3, 4, 5, 6, 7, 8])
+print(np.array_split(a, 3))
+>>> [array([1, 2, 3]), array([4, 5, 6]), array([7, 8])]
+```
+### Shaping Arrays <a name="shape"></a>
+##### TODO
+|Operator|Description|Documentation|
+|:---------|:-------|:------|
+|`other = ndarray.flatten()`|Flattens a 2d array to 1d|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flatten.html)|
+|numpy.flip()|Flips order of elements in 1D array||
+|np.ndarray[::-1]|Same as above||
+|reshape|||
+|squeeze|||
+|expand_dims|||
+
+### Misc <a name="misc"></a>
+|Operator|Description|Documentation|
+|:--------|:--------|:--------|
+|`other = ndarray.flatten()`|Flattens a 2d array to 1d|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flatten.html)|
+|`array = np.transpose(other)`</br> `array.T` |Transpose array|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.transpose.html)|
+|`inverse = np.linalg.inv(matrix)`|Inverse of a given matrix|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.inv.html) |
+</br>
+
+#### Example <a name="inverse of a matrix"></a>
+```python
+# Find inverse of a given matrix
+>>> np.linalg.inv([[3,1],[2,4]])
+array([[ 0.4, -0.1],
+       [-0.2,  0.3]])
+```
+
+## Mathematics <a name="maths"></a>
+
+### Operations <a name="ops"></a>
+| Operator | Description     |Documentation|
+| :------------- | :------------- |:---------|
+|`np.add(x,y)`<br/>`x + y`|Addition|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.add.html)|
+|`np.substract(x,y)`<br/>`x - y`|Subtraction|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.subtract.html#numpy.subtract)|
+|`np.divide(x,y)`<br/>`x / y`|Division|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.divide.html#numpy.divide)|
+|`np.multiply(x,y)`<br/>`x @ y`|Multiplication|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.multiply.html#numpy.multiply)|
+|`np.sqrt(x)`|Square Root|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sqrt.html#numpy.sqrt)|
+|`np.sin(x)`|Element-wise sine|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sin.html#numpy.sin)|
+|`np.cos(x)`|Element-wise cosine|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.cos.html#numpy.cos)|
+|`np.log(x)`|Element-wise natural log|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.log.html#numpy.log)|
+|`np.dot(x,y)`|Dot product|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html)|
+|`np.roots([1,0,-4])`|Roots of a given polynomial coefficients|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.roots.html)|
+
+Remember: NumPy array operations work element-wise.
+
+#### Example <a name="operations-examples"></a>
+```python
+# If a 1d array is added to a 2d array (or the other way), NumPy
+# chooses the array with smaller dimension and adds it to the one
+# with bigger dimension
+a = np.array([1, 2, 3])
+b = np.array([(1, 2, 3), (4, 5, 6)])
+print(np.add(a, b))
+>>> [[2 4 6]
+     [5 7 9]]
+     
+# Example of np.roots
+# Consider a polynomial function (x-1)^2 = x^2 - 2*x + 1
+# Whose roots are 1,1
+>>> np.roots([1,-2,1])
+array([1., 1.])
+# Similarly x^2 - 4 = 0 has roots as x=±2
+>>> np.roots([1,0,-4])
+array([-2.,  2.])
+```
+
+### Comparison
+| Operator | Description | Documentation |
+| :------------- | :------------- |:---------|
+|`==`|Equal|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`!=`|Not equal|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`<`|Smaller than|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`>`|Greater than|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`<=`|Smaller than or equal|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`>=`|Greater than or equal|[link](https://docs.python.org/2/library/stdtypes.html)|
+|`np.array_equal(x,y)`|Array-wise comparison|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.array_equal.html)|
+
+#### Example <a name="comparison-example"></a>
+```python
+# Using comparison operators will create boolean NumPy arrays
+z = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
+c = z < 6
+print(c)
+>>> [ True  True  True  True  True False False False False False]
+```
+### Basic Statistics <a name="stats"></a>
+| Operator | Description    | Documentation |
+| :------------- | :------------- |:--------- |
+|`np.mean(array)`|Mean|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.mean.html#numpy.mean)|
+|`np.median(array)`|Median|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.median.html#numpy.median)|
+|`array.corrcoef()`|Correlation Coefficient|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.corrcoef.html#numpy.corrcoef)|
+|`np.std(array)`|Standard Deviation|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.std.html#numpy.std)|
+
+#### Example <a name="stats-examples"></a>
+```python
+# Statistics of an array
+a = np.array([1, 1, 2, 5, 8, 10, 11, 12])
+
+# Standard deviation
+print(np.std(a))
+>>> 4.2938910093294167
+
+# Median
+print(np.median(a))
+>>> 6.5
+```
+
+
+### More <a name="more"></a>
+| Operator | Description    | Documentation |
+| :------------- | :------------- |:--------- |
+|`array.sum()`|Array-wise sum|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.sum.html)|
+|`array.min()`|Array-wise minimum value|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.min.html)|
+|`array.max(axis=0)`|Maximum value of specified axis||
+|`array.cumsum(axis=0)`|Cumulative sum of specified axis|[link](https://docs.scipy.org/doc/numpy/reference/generated/numpy.cumsum.html)|
+
+</br>
+
+## Slicing and Subsetting <a name="ss"></a>
+|Operator|Description|Documentation|
+| :------------- | :------------- | :------------- |
+|`array[i]`|1d array at index i|[link](https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html)|
+|`array[i,j]`|2d array at index[i][j]|see above|
+|`array[i<4]`|Boolean Indexing, see [Tricks](#tricks)|see above|
+|`array[0:3]`|Select items of index 0, 1 and 2|see above|
+|`array[0:2,1]`|Select items of rows 0 and 1 at column 1|see above|
+|`array[:1]`|Select items of row 0 (equals array[0:1, :])|see above|
+|`array[1:2, :]`|Select items of row 1|see above|
+[comment]: <> (|`array[1,...]`|equals array[1,:,:]|see above|)
+|`array[ : :-1]`|Reverses `array`|see above|
+
+
+#### Examples <a name="exp"></a>
+```python
+b = np.array([(1, 2, 3), (4, 5, 6)])
+
+# The index *before* the comma refers to *rows*,
+# the index *after* the comma refers to *columns*
+print(b[0:1, 2])
+>>> [3]
+
+print(b[:len(b), 2])
+>>> [3 6]
+
+print(b[0, :])
+>>> [1 2 3]
+
+print(b[0, 2:])
+>>> [3]
+
+print(b[:, 0])
+>>> [1 4]
+
+c = np.array([(1, 2, 3), (4, 5, 6)])
+d = c[1:2, 0:2]
+print(d)
+>>> [[4 5]]
+
+```
+
+</br>
+
+## Tricks <a name="tricks"></a>
+This is a growing list of examples. Know a good trick? Let me know in a issue or fork it and create a pull request.
+
+*boolean indexing*
+```python
+# Index trick when working with two np-arrays
+a = np.array([1,2,3,6,1,4,1])
+b = np.array([5,6,7,8,3,1,2])
+
+# Only saves a at index where b == 1
+other_a = a[b == 1]
+#Saves every spot in a except at index where b != 1
+other_other_a = a[b != 1]
+```
+
+```python
+import numpy as np
+x = np.array([4,6,8,1,2,6,9])
+y = x > 5
+print(x[y])
+>>> [6 8 6 9]
+
+# Even shorter
+x = np.array([1, 2, 3, 4, 4, 35, 212, 5, 5, 6])
+print(x[x < 5])
+>>> [1 2 3 4 4]
+
+```
+
+</br>