From af4f92b8b37a9e8736a89c6b355dab128ad11109 Mon Sep 17 00:00:00 2001 From: Henry Date: Tue, 9 Jul 2024 14:56:16 +0200 Subject: [PATCH] :construction: see if emojis are rendere on readthedocs --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 2f014780b..808bbe421 100644 --- a/README.md +++ b/README.md @@ -89,7 +89,7 @@ df_imputed = model.transform(series).unstack() ```
- see log2 transformed DataFrame + :mag: see log2 transformed DataFrame First 10 rows and 10 columns. notice that the indices are named: @@ -245,7 +245,7 @@ Install snakemake e.g. using the provided [`snakemake_env.yml`](https://github.c file as used in [this workflow](https://github.com/RasmussenLab/pimms/blob/HEAD/.github/workflows/ci_workflow.yaml). -> [!NOTE] Snakefile workflow for imputation v1 only support that atm. +> :warning: Snakefile workflow for imputation v1 only support that atm. ```bash snakemake -p -c1 --configfile config/single_dev_dataset/example/config.yaml --use-conda -n # dry-run @@ -325,7 +325,7 @@ assert df_imputed.isna().sum().sum() == 0 df_imputed ``` -> [!NOTE] The imputation is simpler if you use the provide scikit-learn Transformer +> :warning: The imputation is simpler if you use the provide scikit-learn Transformer > interface (see [Tutorial](https://colab.research.google.com/github/RasmussenLab/pimms/blob/HEAD/project/04_1_train_pimms_models.ipynb)). ## Available imputation methods