Data 6 Python Cheatsheet

This cheat sheet has been modified from the Data 6 Python Reference and includes all of the functions and table methods that you will need for the exams.

Built-In Python Functions

Function	Description	Input	Output
str(val)	Converts val to a string	A value of any type (int, float, NoneType, etc.)	The value as a string
int(num)	Converts num to an int	A numerical value (represented as a string or float)	The value as an int
float(num)	Converts num to a float	A numerical value (represented as a string or int)	The value as a float
len(arr)	Returns the length of arr	array or list	int: the length of the array or list
max(arr)	Returns the maximum value in arr	array or list	The maximum value the array (usually an int)
min(arr)	Returns the minimum value in arr	array or list	The minimum value the array (usually an int)
sum(arr)	Returns the sum of the values in arr	array or list	int or float: the sum of the values in the array
abs(num)	Returns the absolute value of num	int or float	int or float
print(input, ...)	Prints the input. Multiple inputs can be passed, and they will be separated by spaces by default.	input: any inputs to print	None
type(object)	Returns the type of object.	object: the object whose type is to be determined	type: the type of the object

NumPy Array Functions

Function	Description	Input	Output
make_array(val1, val2, ...)	Makes a NumPy array with the inputted values	A sequence of values	An array with those values
np.mean(arr) or np.average(arr)	Calculates the average value of arr	An array of numbers	float: The average of the array
np.sum(arr)	Returns the sum of the values in arr	array	int or float: the sum of the values in the array
np.prod(arr)	Returns the product of the values in arr	array	int or float: the product of the values in the array
np.sqrt(num)	Calculates the square root of num	int or float	float : the square root of the number
np.arange(stop), np.arange(start, stop), or np.arange(start, stop, step)	Creates an array of sequential numbers starting at start, going up in increments of step, and going up to but excluding stop. Default start is 0, default step is 1	int or float	array
np.count_nonzero(arr)	Returns the number of non-zero (or True) elements in an array	An array of values	int: the number of non-zero values in arr
np.append(arr, item)	Appends item to the end of arr. Does not modify the original array.	1. array to append to 2. item to append (any type)	array: a new array with the appended item
np.cumsum(arr)	Returns the cumulative sum of the elements in arr, where each element is the sum of all preceding elements including itself	array	array: the cumulative sum of the values in the array
np.diff(arr)	Computes the difference between consecutive elements in arr.	array	array: the differences between consecutive elements in the array containing len(arr) - 1 elements

String Methods

Function	Description	Input	Output
str.split(separator, maxsplit)	Splits str into a list of substrings using the specified separator. If separator is not provided, splits at any whitespace. You can also use the optional argument maxsplit to limit the number of splits.	1. (Optional) separator: the delimiter used to split str 2. (Optional) maxsplit: maximum number of splits	list of substrings
str.join(iterable)	Concatenates the elements in iterable (usually a list or array) into a single string, with each element separated by str.	iterable: an iterable of strings to join (can be an array or list of strings)	string: a single string formed by joining the elements of iterable with the separator str
str.replace(old, new)	Returns a copy of the string with all occurrences of the substring old replaced by new.	old: the substring to be replaced. new: the substring to replace old with.	string: a new string where occurrences of old have been replaced by new.

Tables and Table Methods

Function	Description	Input	Output
Table()	Creates an empty table, usually to extend with data	None	An empty Table
Table().read_table(filename)	Create a table from a data file	string: the name of the file
tbl.with_column(name, values) or tbl.with_columns(n1, v1, n2, v2, ...)	Adds an extra column onto tbl with the label name and values as the column values	1. string: name of the new column 2. array: values in the column	Table: a copy of the original table with the new column(s)
tbl.column(col)	Returns the values in a column in tbl	string or int: the column name or index	array: the values in that column
tbl.num_rows	Compute the number of rows in tbl	None	int: the number of rows in the table
tbl.num_columns	Compute the number of columns in tbl	None	int: the number of columns in the table
tbl.labels	Returns the labels in tbl	None	array: the names of each column as strings
tbl.select(col1, col2, ...)	Creates a copy of tbl only with the selected columns	string or int: the column name(s) or index(es) to be included in the table	Table with the selected columns
tbl.drop(col1, col2, ...)	Creates a copy of tbl without the selected columns	string or int: the column name(s) or index(es) to be dropped from the table	Table without the selected columns
tbl.relabeled(old_label, new_label)	Creates a new table, changing the column name specified by old_label to new_label, and leaves the original table unchanged.	1. string: the old column name 2. string the new column name	Table: a copy of the original table with the changed column name
tbl.show(n)	Displays the first n rows of tbl. If no argument is specified, the function defaults to showing the entire table	(Optional) int: number of rows to be displayed	None (table is displayed)
tbl.sort(column_name)	Sorts the rows of tbl by the values in the column_name column. Defaults to ascending order unless the optional argument descending=True is included.	1. string or int: name or index of the column to sort 2. (Optional) descending=True	Table: a copy of the original table with the column sorted
tbl.where(column, predicate)	Creates a copy of tbl containing only the rows where the value of column matches the predicate. See Table.where predicates below.	1. string or int: column name or index 2. are.(...) predicate	Table: a copy of the original table with only the rows that match the predicate
tbl.take(row_indices)	Creates a table with only the rows at the given indices. row_indices is either an array of indices or an integer corresponding to one index.	int or array: indices of rows to be included in the table	Table: a copy of the original table with only the rows at the given indices
tbl.apply(function) or tbl.apply(function, col1, col2, ...)	Returns an array of values resulting from applying a function to each item in a column.	1. Function: function to apply to column 2. (Optional) string or int: the column name(s) or index(es) to apply the function to	array containing an element for each value in the original column after applying the function to it
tbl.group(column_or_columns, function)	Groups rows in tbl by unique values or combinations of values in a column(s). Multiple columns must be entered as an array of strings. Values in the other columns are aggregated by count (by default) or the optional argument function. You can visualize the group function here.	1. string or array of strings: column(s) on which to group 2. (Optional) Function: function to aggregate values in cells (defaults to counting rows)	Table a new groupped table
tbl.pivot(col1, col2) or tbl.pivot(col1, col2, values, collect)	Creates a pivot table where each unique value in col1 has its own column and each unique value in col2 has its own row. Counts or aggregates values from a third column, collected with some function. If the values and collect arguments are not included, pivot defaults to returning counts in the cells. You can visualize the pivot function here.	1. string: name of the column in tbl whose unique values will make up the columns of the pivot table 2. string: name of column in tbl whose unique values will make up the rows of the pivot table 3. (Optional) string: name of the column in tbl that describes the values of cells in the pivot table 4. (Optional) Function: how the values are collected (e.g. sum or np.mean)	Table: a new pivot table
tblA.join(colA, tblB) or tblA.join(colA, tblB, colB)	Generate a table with the columns of tblA and tblB, containing rows for all values in colA and colB that appear in tblA and tblB, respectively. By default, colB is the same value as colA. colA and colB must be strings specifying column names.	1. string: name of column in tblA with values to join on 2. Table: the other table 3. (Optional) string: the name of the shared column in tblB, if column names are different between the tables	Table: a new combined table
tbl.with_row(values)	Adds a new row with the specified values to tbl	1. list or array: values to add as a new row	Table: a copy of the original table with the new row
tbl.with_rows(list_of_rows)	Adds multiple rows to tbl using a list of rows	1. list of lists or arrays: each list/array represents a new row	Table: a copy of the original table with the new rows

Visualization Functions

Function	Description	Input	Output
tbl.barh(categories) or tbl.barh(categories, values)	Displays a horizontal bar chart with bars for each category in the column categories. values specifies the column corresponding to the size of each bar, but is unnecessary if the table only has two columns. Optional argument overlay (default is True) specifies whether grouped bar charts should be overlaid or on separate plots.	1. string: name of the column with categories 2. (Optional) string: name of the column with values corresponding to the categories	None: draws a bar chart
tbl.hist(column)	Generates a histogram of the numerical values in column. Optional arguments group (to specify categorical column to group on), bins (to specify custom bins), and overlay to specify overlaid or separate histograms.	string: name of the column	None: draws a histogram
tbl.plot(x_column, y_column) or tbl.plot(x_column)	Draws a line plot consisting of one point for each row in tbl. If only x_column is specified, plot will plot the rest of the columns on the y-axis with different colored lines. Optional argument overlay (default is True) specifies whether multiple lines should be overlaid or on separate plots.	1. string: name of the column on the x-axis 2. string: name of the column on the y-axis	None: draws a line graph
tbl.scatter(x_column, y_column)	Draws a scatter plot consisting of one point for each row in tbl. The optional argument fit_line=True can be included to draw a line of best fit through the scatter plot. The optional arguments group (to specify categorical column to group on) and sizes (to specify a numerical column for bubble sizes) can also be used to encode additional variables.	1. string: name of the column on the x-axis 2. string: name of the column on the y-axis 3. (Optional) fit_line=True	None: draws a scatter plot

Table.where Predicates

These functions can be passed in as the second argument to tbl.where(..) and act as a condition by which to select rows from tbl.

Predicate	Description
are.equal_to(Z)	Equal to Z (can be an int, float or string)
are.not_equal_to(Z)	Not equal to ‘Z’ can be a number (int or float) or a string)
are.above(x)	Greater than x
are.above_or_equal_to(x)	Greater than or equal to x
are.below(x)	Less than x
are.below_or_equal_to(x)	Less than or equal to x
are.between(x,y)	Greater than or equal to x and less than y
are.between_or_equal_to(x,y)	Greater than or equal to x, and less than or equal to y
are.strictly_between(x,y)	Greater than x and less than y
are.contained_in(A)	True if it is a substring of A (if A is a **string**) or an element of A (if A` is an array)
are.containing(S)	Contains the string S