analysis_tool Namespace Reference

Documentation for analysis tool. More...

Functions
None	add_df (str name, pd.DataFrame df)
	Adds a new dataframe to the scope.
pd.DataFrame	get_df (str name)
	Returns dataframe by name (or its beginning).
None	show_df (str name, int number_of_rows=5)
	Shows the dataframe.
pd.DataFrame	head (str name, int number_of_rows=5)
	Returns head of the dataframe.
None	remove_df (str name)
	Returns dataframe by name (or its beginning).
int	df_len (str name)
	Returns length of the dataframe.
pd.DataFrame	remove_filename_column (str name)
	Removes "filename" column from the dataframe.
None	initialize_with_archives (str archives_folder, str dataframes_dir)
	Unzips archives and loads dataframes to the scope.
list[str]	dfs_list ()
	Returns a list of dataframe names in the scope.
None	what_is_instruction (str instruction)
	Shows instruction information in a new tab (if such an instruction was found).
dict[str, int]|pd.DataFrame	total_instruction_usage (str name, bool to_dict=True, bool show=True)
	Counts total instruction usage (sum of all values in each column) in the dataframe.
pd.DataFrame	divide_into_categories (str name)
	Divides instructions in the dataframe into categories.
pd.DataFrame	divide_into_groups (str name)
	Divides instructions in the dataframe into groups.
pd.DataFrame	where_instruction (str instruction, str name)
	Leaves only those rows in which the instruction occurs a non-zero number of times.
pd.DataFrame	where_category (str category, str name, bool divide_df=True)
	Leaves only those rows in which instructions of the category occur a non-zero number of times.
pd.DataFrame	where_group (str group, str name, bool divide_df=True)
	Leaves only those rows in which instructions of the group occur a non-zero number of times.
pd.DataFrame	sort_columns_by_sum (str name, bool ascending=False)
	Sorts columns in the dataframe by its sums.
pd.DataFrame	top_popular (str name, int n=10)
	Leaves in the dataframe top n most popular instructions.
pd.DataFrame	top_rare (str name, int n=10)
	Leaves in the dataframe top n the rarest instructions.
None	total_histogram (list[str]|None names=None, bool percent=True, bool ascending=False, int width=2000)
	Builds a histogram of the total instruction usage in dataframes with the names given.
None	total_categories_histogram (list[str]|None names=None, bool percent=True, bool ascending=False, int width=2000)
	Builds a histogram of the total instruction category usage in dataframes with the names given.
None	total_groups_histogram (list[str]|None names=None, bool percent=True, bool ascending=False, int width=2000)
	Builds a histogram of the total instruction group usage in dataframes with the names given.

Detailed Description

Documentation for analysis tool.

Function Documentation

add_df()

None analysis_tool.add_df	(	str	name,
		pd.DataFrame	df
	)

Adds a new dataframe to the scope.

Parameters

name	Name of the dataframe.
df	Dataframe.

df_len()

int analysis_tool.df_len

(

str

name

)

Returns length of the dataframe.

Parameters

name	Name of the dataframe or its beginning.

Returns

Length of the dataframe.

dfs_list()

list[str] analysis_tool.dfs_list

(

)

Returns a list of dataframe names in the scope.

Returns

List of dataframe names.

divide_into_categories()

pd.DataFrame analysis_tool.divide_into_categories

(

str

name

)

Divides instructions in the dataframe into categories.

Parameters

name	Name of the dataframe or its beginning.

Returns

Dataframe with instruction categories.

divide_into_groups()

pd.DataFrame analysis_tool.divide_into_groups

(

str

name

)

Divides instructions in the dataframe into groups.

Parameters

name	Name of the dataframe or its beginning.

Returns

Dataframe with instruction groups.

get_df()

pd.DataFrame analysis_tool.get_df

(

str

name

)

Returns dataframe by name (or its beginning).

Parameters

name	Name of the dataframe or its beginning.

Returns

Dataframe.

head()

pd.DataFrame analysis_tool.head	(	str	name,
		int	number_of_rows = 5
	)

Returns head of the dataframe.

Parameters

name	Name of the dataframe or its beginning.
number_of_rows	Number of rows in head. Default: 5.

Returns

Head of the dataframe.

initialize_with_archives()

None analysis_tool.initialize_with_archives	(	str	archives_folder,
		str	dataframes_dir
	)

Unzips archives and loads dataframes to the scope.

Parameters

archives_folder	Path to the folder with archives.
dataframes_dir	Path to the folder in which unzipped dataframes will be placed.

remove_df()

None analysis_tool.remove_df

(

str

name

)

Returns dataframe by name (or its beginning).

Parameters

name	Name of the dataframe or its beginning.

remove_filename_column()

pd.DataFrame analysis_tool.remove_filename_column

(

str

name

)

Removes "filename" column from the dataframe.

Parameters

name	Name of the dataframe or its beginning.

Returns

Dataframe without "filename" column.

show_df()

None analysis_tool.show_df	(	str	name,
		int	number_of_rows = 5
	)

Shows the dataframe.

Parameters

name	Name of the dataframe or its beginning.
number_of_rows	Number of rows to show. Default: 5.

sort_columns_by_sum()

pd.DataFrame analysis_tool.sort_columns_by_sum	(	str	name,
		bool	ascending = False
	)

Sorts columns in the dataframe by its sums.

Parameters

name	Name of the dataframe or its beginning.
ascending	If True, the dataframe columns will be sorted in ascending order, otherwise - in descending order. Default: False.

Returns

Dataframe with sorted columns.

top_popular()

pd.DataFrame analysis_tool.top_popular	(	str	name,
		int	n = 10
	)

Leaves in the dataframe top n most popular instructions.

Parameters

name	Name of the dataframe or its beginning.
n	Number of instructions. Default: 10.

Returns

: Dataframe with top n most popular instructions.

top_rare()

pd.DataFrame analysis_tool.top_rare	(	str	name,
		int	n = 10
	)

Leaves in the dataframe top n the rarest instructions.

Parameters

name	Name of the dataframe or its beginning.
n	Number of instructions. Default: 10.

Returns

Dataframe with top n the rarest instructions.

total_categories_histogram()

None analysis_tool.total_categories_histogram	(	list[str] | None	names = None,
		bool	percent = True,
		bool	ascending = False,
		int	width = 2000
	)

Builds a histogram of the total instruction category usage in dataframes with the names given.

Parameters

names	None or list of dataframe names (or their beginnings). If None, all dataframes in the scope will be used. Default: None.
percent	If True, the histogram will be built by percentage, not by absolute values. Default: True.
ascending	If True, the histogram columns will be sorted in ascending order, otherwise - in descending order. Default: False.
width	Width of the histogram. Default: 2000.

total_groups_histogram()

None analysis_tool.total_groups_histogram	(	list[str] | None	names = None,
		bool	percent = True,
		bool	ascending = False,
		int	width = 2000
	)

Builds a histogram of the total instruction group usage in dataframes with the names given.

Parameters

names	None or list of dataframe names (or their beginnings). If None, all dataframes in the scope will be used. Default: None.
percent	If True, the histogram will be built by percentage, not by absolute values. Default: True.
ascending	If True, the histogram columns will be sorted in ascending order, otherwise - in descending order. Default: False.
width	Width of the histogram. Default: 2000.

total_histogram()

None analysis_tool.total_histogram	(	list[str] | None	names = None,
		bool	percent = True,
		bool	ascending = False,
		int	width = 2000
	)

Builds a histogram of the total instruction usage in dataframes with the names given.

Parameters

names	None or list of dataframe names (or their beginnings). If None, all dataframes in the scope will be used. Default: None.
percent	If True, the histogram will be built by percentage, not by absolute values. Default: True.
ascending	If True, the histogram columns will be sorted in ascending order, otherwise - in descending order. Default: False.
width	Width of the histogram. Default: 2000.

total_instruction_usage()

dict[str, int] | pd.DataFrame analysis_tool.total_instruction_usage	(	str	name,
		bool	to_dict = True,
		bool	show = True
	)

Counts total instruction usage (sum of all values in each column) in the dataframe.

Parameters

name	Name of the dataframe or its beginning.
to_dict	If True, function returns the result in the form of a dictionary. Default: True.
show	Pretty print a result. Default: True.

Returns

Dictionary or dataframe with total instruction usage.

what_is_instruction()

None analysis_tool.what_is_instruction

(

str

instruction

)

Shows instruction information in a new tab (if such an instruction was found).

Parameters

instruction

Instruction.

where_category()

pd.DataFrame analysis_tool.where_category	(	str	category,
		str	name,
		bool	divide_df = True
	)

Leaves only those rows in which instructions of the category occur a non-zero number of times.

Parameters

category	Category.
name	Name of the dataframe or its beginning.
divide_df	If True, function will divide instructions in the dataframe into categories. Default: True.

Returns

Dataframe with selected rows.

where_group()

pd.DataFrame analysis_tool.where_group	(	str	group,
		str	name,
		bool	divide_df = True
	)

Leaves only those rows in which instructions of the group occur a non-zero number of times.

Parameters

group	Group.
name	Name of the dataframe or its beginning.
divide_df	If True, function will divide instructions in the dataframe into groups. Default: True.

Returns

Dataframe with selected rows.

where_instruction()

pd.DataFrame analysis_tool.where_instruction	(	str	instruction,
		str	name
	)

Leaves only those rows in which the instruction occurs a non-zero number of times.

Parameters

instruction	Instruction.
name	Name of the dataframe or its beginning.

Returns

Dataframe with selected rows.