Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Pandas-friendly column names #443

Merged
merged 16 commits into from
Dec 8, 2024
14 changes: 7 additions & 7 deletions .github/workflows/python_tests.yml
Original file line number Diff line number Diff line change
Expand Up @@ -2,9 +2,9 @@ name: Python tests

on:
push:
branches: [master, develop]
branches: [main]
pull_request:
branches: [master, develop]
branches: [main]

jobs:
build:
Expand All @@ -20,10 +20,10 @@ jobs:
FORCE_COLOR: true

steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4

- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v1
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}

Expand All @@ -39,20 +39,20 @@ jobs:
- name: Build docs
if: ${{ matrix.platform == 'ubuntu-latest' && matrix.python-version == 3.9 }}
run: |
pip install --upgrade sphinx sphinx_bootstrap_theme numpydoc sphinx-copybutton sphinx-panels
pip install .[docs]
make -C docs clean
make -C docs html

- name: Upload doc build artifacts
if: ${{ matrix.platform == 'ubuntu-latest' && matrix.python-version == 3.9 }}
uses: actions/upload-artifact@v1
uses: actions/upload-artifact@v4
with:
name: docs-artifact
path: docs/build/html

- name: Upload coverage report
if: ${{ matrix.platform == 'ubuntu-latest' && matrix.python-version == 3.9 }}
uses: codecov/codecov-action@v1
uses: codecov/codecov-action@v4
with:
token: c6ed6ca6-a040-4f23-9ebf-8c474c998097
file: ./coverage.xml
20 changes: 10 additions & 10 deletions README.rst
Original file line number Diff line number Diff line change
Expand Up @@ -157,7 +157,7 @@ Click on the link below and navigate to the notebooks/ folder to run a collectio
:widths: auto

====== ===== ============= ======= ============= ========= ====== =======
T dof alternative p-val CI95% cohen-d BF10 power
T dof alternative p_val CI95 cohen_d BF10 power
====== ===== ============= ======= ============= ========= ====== =======
-3.401 58 two-sided 0.001 [-1.68 -0.43] 0.878 26.155 0.917
====== ===== ============= ======= ============= ========= ====== =======
Expand All @@ -175,7 +175,7 @@ Click on the link below and navigate to the notebooks/ folder to run a collectio
:widths: auto

=== ===== =========== ======= ====== =======
n r CI95% p-val BF10 power
n r CI95 p_val BF10 power
=== ===== =========== ======= ====== =======
30 0.595 [0.3 0.79] 0.001 69.723 0.950
=== ===== =========== ======= ====== =======
Expand All @@ -196,7 +196,7 @@ Click on the link below and navigate to the notebooks/ folder to run a collectio
:widths: auto

=== ===== =========== ======= =======
n r CI95% p-val power
n r CI95 p_val power
=== ===== =========== ======= =======
30 0.576 [0.27 0.78] 0.001 0.933
=== ===== =========== ======= =======
Expand Down Expand Up @@ -244,7 +244,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

======== ======= ==== ===== ======= ======= =======
Source SS DF MS F p-unc np2
Source SS DF MS F p_unc np2
======== ======= ==== ===== ======= ======= =======
Group 5.460 1 5.460 5.244 0.023 0.029
Within 185.343 178 1.041 nan nan nan
Expand All @@ -263,7 +263,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

======== ======= ==== ===== ======= ======= ======= =======
Source SS DF MS F p-unc ng2 eps
Source SS DF MS F p_unc ng2 eps
======== ======= ==== ===== ======= ======= ======= =======
Time 7.628 2 3.814 3.913 0.023 0.04 0.999
Error 115.027 118 0.975 nan nan nan nan
Expand All @@ -287,7 +287,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

========== ======= ======= ======== ============ ====== ====== ============= ======= ======== ========== ====== ========
Contrast A B Paired Parametric T dof alternative p-unc p-corr p-adjust BF10 hedges
Contrast A B Paired Parametric T dof alternative p_unc p_corr p_adjust BF10 hedges
========== ======= ======= ======== ============ ====== ====== ============= ======= ======== ========== ====== ========
Time August January True True -1.740 59.000 two-sided 0.087 0.131 fdr_bh 0.582 -0.328
Time August June True True -2.743 59.000 two-sided 0.008 0.024 fdr_bh 4.232 -0.483
Expand All @@ -310,7 +310,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

=========== ===== ===== ===== ===== ===== ======= ===== =======
Source SS DF1 DF2 MS F p-unc np2 eps
Source SS DF1 DF2 MS F p_unc np2 eps
=========== ===== ===== ===== ===== ===== ======= ===== =======
Group 5.460 1 58 5.460 5.052 0.028 0.080 nan
Time 7.628 2 116 3.814 4.027 0.020 0.065 0.999
Expand All @@ -334,7 +334,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

=== === ======== ============= === ===== ============= ======= ====== =======
X Y method alternative n r CI95% p-unc BF10 power
X Y method alternative n r CI95 p_unc BF10 power
=== === ======== ============= === ===== ============= ======= ====== =======
X Y pearson two-sided 30 0.366 [0.01 0.64] 0.047 1.500 0.525
X Z pearson two-sided 30 0.251 [-0.12 0.56] 0.181 0.534 0.272
Expand Down Expand Up @@ -374,7 +374,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

========= ====== ===== ====== ====== ===== ======== ========== ===========
names coef se T pval r2 adj_r2 CI[2.5%] CI[97.5%]
names coef se T pval r2 adj_r2 CI2.5 CI97.5
========= ====== ===== ====== ====== ===== ======== ========== ===========
Intercept 4.650 0.841 5.530 0.000 0.139 0.076 2.925 6.376
X 0.143 0.068 2.089 0.046 0.139 0.076 0.003 0.283
Expand All @@ -394,7 +394,7 @@ The `pingouin.normality` function works with lists, arrays, or pandas DataFrame
:widths: auto

======== ====== ===== ====== ========== =========== =====
path coef se pval CI[2.5%] CI[97.5%] sig
path coef se pval CI2.5 CI97.5 sig
======== ====== ===== ====== ========== =========== =====
Z ~ X 0.103 0.075 0.181 -0.051 0.256 No
Y ~ Z 0.018 0.171 0.916 -0.332 0.369 No
Expand Down
2 changes: 1 addition & 1 deletion docs/contributing.rst
Original file line number Diff line number Diff line change
Expand Up @@ -80,7 +80,7 @@ To inspect these build artifacts, follow these steps:

Screenshot of the GitHub checks dropdown menu

* Click on the check that starts with ``Python tests / build (ubuntu-latest, 3.8)``
* Click on the check that starts with ``Python tests / build (ubuntu-latest, 3.9)``
* Now in the top right corner of the opening window, you will see a small dropdown menu called "Artifacts"

.. figure:: /pictures/github_build_artifacts.png
Expand Down
20 changes: 10 additions & 10 deletions docs/index.rst
Original file line number Diff line number Diff line change
Expand Up @@ -135,7 +135,7 @@ Quick start
:widths: auto

====== ===== ============= ======= ============= ========= ====== =======
T dof alternative p-val CI95% cohen-d BF10 power
T dof alternative p_val CI95 cohen_d BF10 power
====== ===== ============= ======= ============= ========= ====== =======
-3.401 58 two-sided 0.001 [-1.68 -0.43] 0.878 26.155 0.917
====== ===== ============= ======= ============= ========= ====== =======
Expand All @@ -153,7 +153,7 @@ Quick start
:widths: auto

=== ===== =========== ======= ====== =======
n r CI95% p-val BF10 power
n r CI95 p_val BF10 power
=== ===== =========== ======= ====== =======
30 0.595 [0.3 0.79] 0.001 69.723 0.950
=== ===== =========== ======= ====== =======
Expand All @@ -174,7 +174,7 @@ Quick start
:widths: auto

=== ===== =========== ======= =======
n r CI95% p-val power
n r CI95 p_val power
=== ===== =========== ======= =======
30 0.576 [0.27 0.78] 0.001 0.933
=== ===== =========== ======= =======
Expand Down Expand Up @@ -235,7 +235,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

======== ======= ==== ===== ======= ======= =======
Source SS DF MS F p-unc np2
Source SS DF MS F p_unc np2
======== ======= ==== ===== ======= ======= =======
Group 5.460 1 5.460 5.244 0.023 0.029
Within 185.343 178 1.041 nan nan nan
Expand All @@ -254,7 +254,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

======== ======= ==== ===== ======= ======= ======= =======
Source SS DF MS F p-unc ng2 eps
Source SS DF MS F p_unc ng2 eps
======== ======= ==== ===== ======= ======= ======= =======
Time 7.628 2 3.814 3.913 0.023 0.04 0.999
Error 115.027 118 0.975 nan nan nan nan
Expand All @@ -278,7 +278,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

========== ======= ======= ======== ============ ====== ====== ============= ======= ======== ========== ====== ========
Contrast A B Paired Parametric T dof alternative p-unc p-corr p-adjust BF10 hedges
Contrast A B Paired Parametric T dof alternative p_unc p_corr p_adjust BF10 hedges
========== ======= ======= ======== ============ ====== ====== ============= ======= ======== ========== ====== ========
Time August January True True -1.740 59.000 two-sided 0.087 0.131 fdr_bh 0.582 -0.328
Time August June True True -2.743 59.000 two-sided 0.008 0.024 fdr_bh 4.232 -0.483
Expand All @@ -301,7 +301,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

=========== ===== ===== ===== ===== ===== ======= ===== =======
Source SS DF1 DF2 MS F p-unc np2 eps
Source SS DF1 DF2 MS F p_unc np2 eps
=========== ===== ===== ===== ===== ===== ======= ===== =======
Group 5.460 1 58 5.460 5.052 0.028 0.080 nan
Time 7.628 2 116 3.814 4.027 0.020 0.065 0.999
Expand All @@ -325,7 +325,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

=== === ======== ============= === ===== ============= ======= ====== =======
X Y method alternative n r CI95% p-unc BF10 power
X Y method alternative n r CI95 p_unc BF10 power
=== === ======== ============= === ===== ============= ======= ====== =======
X Y pearson two-sided 30 0.366 [0.01 0.64] 0.047 1.500 0.525
X Z pearson two-sided 30 0.251 [-0.12 0.56] 0.181 0.534 0.272
Expand Down Expand Up @@ -365,7 +365,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

========= ====== ===== ====== ====== ===== ======== ========== ===========
names coef se T pval r2 adj_r2 CI[2.5%] CI[97.5%]
names coef se T pval r2 adj_r2 CI2.5 CI97.5
========= ====== ===== ====== ====== ===== ======== ========== ===========
Intercept 4.650 0.841 5.530 0.000 0.139 0.076 2.925 6.376
X 0.143 0.068 2.089 0.046 0.139 0.076 0.003 0.283
Expand All @@ -385,7 +385,7 @@ The :py:func:`pingouin.normality` function works with lists, arrays, or pandas D
:widths: auto

======== ====== ===== ====== ========== =========== =====
path coef se pval CI[2.5%] CI[97.5%] sig
path coef se pval CI2.5 CI97.5 sig
======== ====== ===== ====== ========== =========== =====
Z ~ X 0.103 0.075 0.181 -0.051 0.256 No
Y ~ Z 0.018 0.171 0.916 -0.332 0.369 No
Expand Down
Loading
Loading