⬆️ add pandas 2 support (#72)

* ⬆️ add pandas 2 support

* 🍱 run notebooks

* 💄 reformat with precommit

* 🔧 Move pandas down in deps

* 🔧 remove version req from pandas

* 💄 precommit run

---------

Co-authored-by: buettnerm <maren.buettner@dzne.de>

docs/tutorials/preprocessing.ipynb

@@ -187,7 +187,8 @@
     "In the next step, we normalize the data. By default, normalization is an inplace operation, i.e. we only create a new anndata object, if we set the argument `inplace=False`. We demonstrate three different normalization methods that are build in `pytometry`:\n",
     "* arcsinh \n",
     "* logicle \n",
-    "* bi-exponential"
+    "* bi-exponential\n",
+    "* auto-logicle"
    ]
   },
   {
@@ -216,6 +217,15 @@
    "source": [
     "adata_biex = pm.tl.normalize_biExp(adata, inplace=False)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "adata_autologicle = pm.tl.normalize_autologicle(adata, inplace=False)"
+   ]
   }
  ],
  "metadata": {
@@ -234,7 +244,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.9.19"
   },
   "vscode": {
    "interpreter": {

docs/tutorials/quickstart.ipynb

@@ -18,7 +18,8 @@
    "source": [
     "import pytometry as pm\n",
     "import readfcs\n",
-    "import anndata"
+    "import anndata\n",
+    "from matplotlib import rcParams"
    ]
   },
   {
@@ -114,7 +115,16 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pm.pl.scatter_density(adata, x_lim=[-1, 2.7e5])"
+    "rcParams[\"figure.figsize\"] = (6, 5)\n",
+    "pm.pl.scatter_density(adata, x_lim=[-5e3, 2e5], y_lim=[-5e3, 2e5])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "29e11870",
+   "metadata": {},
+   "source": [
+    "Compensate with the compensation matrix that is deposited in the FCS file. The `compensate` function also accepts a custom compensation matrix. "
    ]
   },
   {
@@ -127,6 +137,14 @@
     "pm.pp.compensate(adata)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "2200fd8d",
+   "metadata": {},
+   "source": [
+    "For normalization, `pytometry` provides several different approaches:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

pyproject.toml

@@ -15,7 +15,7 @@ requires-python = '>= 3.9'
 dependencies = [
     "numpy>=1.20.0",
     "numba>=0.57",
-    "pandas<2.0.0,>=1.5.3",
+    "pandas",
     "anndata",
     "scanpy",
     "scipy",
@@ -25,6 +25,7 @@ dependencies = [
     "flowutils",
     "consensusclustering",
     "minisom"
+
 ]
 
 [project.urls]