Python data visualisation
Project description
datavision
Python data visualisation
setup
pip install datavision
qunti and zus lists
Qunti (群体, groups) are lists that act
as dictionaries that can contain duplicate keys and
as sets for the purposes of enabling set-like operations for qunti objects, such as symmetric difference, intersection and update operations.
Qunti are composed of multiple zu (组, group) objects.
qunti operations
In an update operation, one qunti is used to update another. Any zus in the updating qunti that are not in the updated qunti are appended to the updated qunti. Any zus that are in the updating qunti and the updated qunti replace the corresponding zus in the updated qunti.
The following example illustrates a qunti update operation in which an alpha zus is replaced and a delta zus is appended:
# example qunti update:
a = [['alpha', '10'], ['beta', '20'], ['gamma', '30'], ['gamma', '15']]
b = [['delta', '40'], ['alpha', '50']]
# update of a with b:
a = [['beta', '20'], ['gamma', '30'], ['gamma', '15'], ['delta', '40'], ['alpha', '50']]
The following example illustrates qunti symmetric difference, intersection and update operations. In the update operation, two old gamma zus are replaced by a single new gamma zu:
# example qunti symmetric difference, intersection and update:
a = [['alpha', '10'], ['beta', '20'], ['gamma', '30'], ['gamma', '15']]
b = [['delta', '40'], ['alpha', '50'], ['gamma', '25']]
# symmetric difference of a and b:
[['beta', '20'], ['delta', '40']]
# intersection of a and b:
[['alpha', '10'], ['gamma', '30'], ['gamma', '15'], ['alpha', '50'], ['gamma', '25']]
# update of a with b:
a = [['beta', '20'], ['delta', '40'], ['alpha', '50'], ['gamma', '25']]
data visualisation
Datavision provides utilities for data visualisation.
matrices as colormaps
histograms
terminal graphs and histograms
│ ┼+79.548 ○ │ │ ○ │ │ ○ │ │ ○ ◽ ◽ ◽ ○ │ ◽ ○ │ ○ ◽ ───○┼──────○───────○───────────────────────◽────────────────────────────────┼─── │ +0.046 ◽ +8.97638 │ │ ◽ │ │ ◽ ┼-48.228 │ ◽ │
│ ┼+75503.2 ∘∘|∘ ∘||||∘ ||||||∘ ∘||||||| ||||||||∘ ∘||||||||| ||||||||||∘ ∘||||||||||| |||||||||||∘ ∘|||||||||||| |||||||||||||∘ ||||||||||||||∘ ∘|||||||||||||||∘ ∘|||||||||||||||||∘ ∘|||||||||||||||||||∘ ∘∘∘||||||||||┼+1603.2|||∘∘∘ ──┼--------------------------------------------┼── -4.69099 │ +4.6147
echo "0, 1, 4, 9, 16, 25, 36, 49, 64, 81" | datavision_TTY_plot.py
combinations of variables
parallel coordinates
FFT
time graphs
Bollinger bands
graphs
databases
Datavision features some scripts for interacting with databases:
change_field_name_database_SQLite.py
duplicates_database_SQLite.py
view_database_SQLite.py
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file datavision-2018.1.8.2333.tar.gz
.
File metadata
- Download URL: datavision-2018.1.8.2333.tar.gz
- Upload date:
- Size: 38.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a104c9393f5d7be8d934ed6b7b98145c63937bb6e418fe685079ada1f081d272 |
|
MD5 | 553adaa5e4a4da44cb02cc2d4980b4f7 |
|
BLAKE2b-256 | 0e30e07aae4d4ee35eb03ac3555ab3176008bc453e960478da03c5c48320ff17 |