other:python:jyp_steps
Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
other:python:jyp_steps [2019/07/09 14:39] jypeter [Matplotlib] Added note about alpha/transparency |
other:python:jyp_steps [2019/08/09 09:40] jypeter [Useful matplotlib reference pages] improved colorbar |
||
|---|---|---|---|
| Line 290: | Line 290: | ||
| * ''cmap.set_over(color='k')'': color to be used for high out-of-range values | * ''cmap.set_over(color='k')'': color to be used for high out-of-range values | ||
| * ''cmap.set_under(color='k')'': color to be used for low out-of-range values | * ''cmap.set_under(color='k')'': color to be used for low out-of-range values | ||
| - | * [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.colorbar|colorbar]] and ([[https://matplotlib.org/gallery/images_contours_and_fields/contourf_demo.html|contourf + colorbar demo]]) | + | * [[https://matplotlib.org/api/_as_gen/matplotlib.figure.Figure.html#matplotlib.figure.Figure.colorbar|colorbar]] |
| + | * [[https://matplotlib.org/gallery/subplots_axes_and_figures/colorbar_placement.html|Placing colorbars demo]] | ||
| + | * [[https://matplotlib.org/gallery/images_contours_and_fields/contourf_demo.html|contourf + colorbar demo]] | ||
| * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.text.html|text(...)]] and [[https://matplotlib.org/tutorials/text/annotations.html|annotations]] | * [[https://matplotlib.org/api/_as_gen/matplotlib.pyplot.text.html|text(...)]] and [[https://matplotlib.org/tutorials/text/annotations.html|annotations]] | ||
| * Some titles: | * Some titles: | ||
| Line 421: | Line 423: | ||
| Where: [[http://pandas.pydata.org|Pandas web site]] | Where: [[http://pandas.pydata.org|Pandas web site]] | ||
| - | JYP's comment: pandas is supposed to be quite good for loading, processing and plotting time series, without writing custom code. You should at least have a quick look at: | + | JYP's comment: pandas is supposed to be quite good for loading, processing and plotting time series, without writing custom code. It is **very convenient for processing tables in xlsx files** (or csv, etc...). You should at least have a quick look at: |
| - | * The [[http://www.scipy-lectures.org/packages/statistics/index.html|Statistics in Python]] tutorial that combines Pandas, [[http://statsmodels.sourceforge.net/|Statsmodels]] and [[http://seaborn.pydata.org/|Seaborn]] | + | |
| - | * the cheat sheet on the [[https://www.enthought.com/services/training/pandas-mastery-workshop/|Enthought workshops advertising page]] | + | * Some //Cheat Sheets// (in the following order): |
| - | * the cheat sheet on the [[https://github.com/pandas-dev/pandas/tree/master/doc/cheatsheet|github Pandas doc page]] | + | - Basics: [[http://datacamp-community-prod.s3.amazonaws.com/dbed353d-2757-4617-8206-8767ab379ab3|Pandas basics]] (associated with the [[https://www.datacamp.com/community/blog/python-pandas-cheat-sheet|Pandas Cheat Sheet for Data Science in Python]] pandas introduction page) |
| + | - Intermediate: [[https://github.com/pandas-dev/pandas/tree/master/doc/cheatsheet|github Pandas doc page]] | ||
| + | - Advanced: the cheat sheet on the [[https://www.enthought.com/services/training/pandas-mastery-workshop/|Enthought workshops advertising page]] | ||
| + | * Some tutorials: | ||
| + | * [[https://www.datacamp.com/community/blog/python-pandas-cheat-sheet|Pandas Cheat Sheet for Data Science in Python]] pandas introduction page | ||
| + | * The [[http://www.scipy-lectures.org/packages/statistics/index.html|Statistics in Python]] tutorial that combines Pandas, [[http://statsmodels.sourceforge.net/|Statsmodels]] and [[http://seaborn.pydata.org/|Seaborn]] | ||
| ===== Scipy Lecture Notes ===== | ===== Scipy Lecture Notes ===== | ||
other/python/jyp_steps.txt · Last modified: 2024/03/07 10:15 by jypeter
