Created by Nishant Kheterpal

In the examples in the left column, `np`

refers to the NumPy module, as usual. Everything else is a function, a method, an example of an argument to a function or method, or an example of an object we might call the method on. For example, `tbl`

refers to a table, `array`

refers to an array, and `num`

refers to a number. `array.item(0)`

is an example call for the method `item`

, and in that example, `array`

is the name previously given to some array.

Name | Chapter | Description |
---|---|---|

`Table()` |
6 | Create an empty table, usually to extend with data |

`Table().read_table(filename)` |
6 | Create a table from a data file |

`tbl.with_columns(name, values) tbl.with_columns(n1, v1, n2, v2,...)` |
6 | A table with an additional or replaced column or columns. `name` is a string for the name of a column, `values` is an array |

`tbl.column(column_name_or_index)` |
6 | The values of a column (an array) |

`tbl.num_rows` |
6 | Compute the number of rows in a table |

`tbl.num_columns` |
6 | Compute the number of columns in a table |

`tbl.labels` |
6 | Lists the column labels in a table |

`tbl.select(col1, col2, ...)` |
6 | Create a copy of a table with only some of the columns. Each column is the column name or index. |

`tbl.drop(col1, col2, ...)` |
6 | Create a copy of a table without some of the columns. Each column is the column name or index. |

`tbl.relabel(old_label, new_label)` |
6 | Modifies the existing table in place, changing the column heading in the first argument to the second |

`tbl.relabeled(old_label, new_label)` |
6 | Returns a new table with the column heading in the first argument changed to the second |

`tbl.sort(column_name_or_index)` |
6.1 | Create a copy of a table sorted by the values in a column. Defaults to ascending order unless "descending = True" is included |

`tbl.where(column, predicate)` |
6.2 | Create a copy of a table with only the rows that match some predicate See `Table.where` predicates below |

`tbl.take(row_indices)` |
6.2 | A table with only the rows at the given indices. `row_indices` is an array of indices. |

`tbl.scatter(x_column, y_column)` |
7 | Draws a scatter plot consisting of one point for each row of the table. Note that `x_column` and `y_column` must be strings specifying column names. |

`tbl.plot(x_column, y_column)` |
7 | Draw a line graph consisting of one point for each row of the table. |

`tbl.barh(categories) tbl.barh(categories, values)` |
7.1 | Displays a bar chart with bars for each category in a column, with height proportional to the corresponding frequency. values argument unnecessary if table has only a column of categories and a column of values. |

`tbl.hist(column, unit, bins)` |
7.2 | Generates a histogram of the numerical values in a column. `unit` and `bins` are optional arguments, used to label the axes and group the values into intervals (bins), respectively. Bins have the form [a, b). |

`tbl.apply(function, column)` |
8.1 | Returns an array of values resulting from applying a function to each item in a column. |

`tbl.group(column_or_columns, func)` |
8.2 | Group rows by unique values or combinations of values in a column(s). Multiple columns must be entered in array or list form. Other values aggregated by count (default) or optional argument `func` . |

`tbl.pivot(col1, col2, vals, collect) tbl.pivot(col1, col2)` |
8.3 | A pivot table where each unique value in `col1` has its own column and each unique value in c`col2` has its own row. Count or aggregate values from a third column, collect with some function. Default `vals` and `collect` return counts in cells. |

`tblA.join(colA, tblB, colB) tblA.join(colA, tblB)` |
8.4 | Generate a table with the columns of tblA and tblB, containing rows for all values of a column that appear in both tables. Default `colB` is `colA` . `colA` and `colB` must be strings specifying column names. |

`tbl.sample(n) tbl.sample(n, with_replacement)` |
10 | A new table where `n` rows are randomly sampled from the original table. Default is with replacement. For sampling without replacement, use argument `with_replacement=False` . For a non-uniform sample, provide a third argument `weights=distribution` where `distribution` is an array or list containing the probability of each row. |

`sample_proportions(sample_size, model_proportions` |
11.1 | `Sample_size` should be an integer, `model_proportions` an array of probabilities that sum up to 1. The function samples `sample_size` objects from the distribution specified by `model_proportions` . It returns an array with the same size as `model_proportions` . Each item in the array corresponds to the proportion of times it was sampled out of the `sample_size` times. |

Name | Chapter | Description |
---|---|---|

`max(array)` |
3.3 | Returns the maximum value of an array |

`min(array)` |
3.3 | Returns the minimum value of an array |

`sum(array)` |
3.3 | Returns the sum of the values in an array |

`abs(num), np.abs(array)` |
3.3 | Take the absolute value of number or each number in an array. |

`round(num), np.round(array)` |
3.3 | Round number or array of numbers to the nearest integer. |

`len(array)` |
3.3 | Returns the length (number of elements) of an array |

`make_array(val1, val2, ...)` |
5 | Makes a numpy array with the values passed in |

`np.average(array) np.mean(array)` |
5.1 | Returns the mean value of an array |

`np.diff(array)` |
5.1 | Returns a new array of size `len(arr)-1` with elements equal to the difference between adjacent elements; val_2 - val_1, val_3 - val_2, etc. |

`np.sqrt(array)` |
5.1 | Returns an array with the square root of each element |

`np.arange(start, stop, step) np.arange(start, stop) np.arange(stop)` |
5.2 | An array of numbers starting with `start` , going up in increments of `step` , and going up to but excluding `stop` . When `start` and/or `step` are left out, default values are used in their place. Default step is 1; default start is 0. |

`array.item(index)` |
5.3 | Returns the i-th item in an array (remember Python indices start at 0!) |

`np.random.choice(array, n) np.random.choice(array)` |
9 | Picks one (by default) or some number 'n' of items from an array at random. By default, with replacement. |

`np.count_nonzero(array)` |
9 | Returns the number of non-zero (or `True` ) elements in an array. |

`np.append(array, item)` |
9.2 | Returns a copy of the input array with `item` (must be the same type as the other entries in the array) appended to the end. |

`percentile(percentile, array)` |
12.1 | Returns the corresponding percentile of an array. |