Merge pull request #96 from aleaf/main

Fix remaining part 0 notebook test fails

notebooks/part0_python_intro/05_numpy.ipynb

@@ -113,13 +113,14 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "#Note that the following does not work.  Brackets are required so that the input is a list.\n",
-    "a = np.array(1, 2, 3)"
+    "Note that the following does not work.  Brackets are required so that the input is a list.\n",
+    "\n",
+    "```python\n",
+    "a = np.array(1, 2, 3)\n",
+    "```"
    ]
   },
   {
@@ -572,7 +573,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "a[slice(5, None, 5)]"
+    "a[slice(50, None, 5)]"
    ]
   },
   {

notebooks/part0_python_intro/06_matplotlib.ipynb

@@ -13,15 +13,6 @@
     "The other notebooks in this lecture series are indexed at [https://github.com/jrjohansson/scientific-python-lectures](https://github.com/jrjohansson/scientific-python-lectures)."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%matplotlib inline"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1175,7 +1166,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

notebooks/part0_python_intro/08_pandas.ipynb

@@ -29,18 +29,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os\n",
+    "from pathlib import Path\n",
     "import numpy as np\n",
     "import matplotlib as mpl\n",
     "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
     "from dataretrieval import nwis\n",
-    "import datetime \n",
     "import statsmodels.api as sm\n",
     "from matplotlib.backends.backend_pdf import PdfPages\n",
     "from scipy.signal import detrend\n",
     "\n",
-    "data_path = os.path.join(\"data\", \"pandas\")"
+    "data_path = Path(\"data\", \"pandas\")"
    ]
   },
   {
@@ -80,7 +79,7 @@
    "source": [
     "info, metadata = nwis.get_info(bBox=[str(i) for i in bbox])\n",
     "info\n",
-    "info.to_csv(os.path.join(data_path, \"site_info.csv\"), index=False)"
+    "info.to_csv(data_path / \"site_info.csv\", index=False)"
    ]
   },
   {
@@ -107,16 +106,6 @@
     "   - `.describe()`: statistically describe the data"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "935770bd-2b49-49c0-9249-8a2c4883bb7f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "info = pd.read_csv(os.path.join(data_path, \"site_info.csv\"))"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -322,7 +311,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "csv_file = os.path.join(data_path, \"RussianRiverGWsites.csv\")\n",
+    "csv_file = data_path / \"RussianRiverGWsites.csv\"\n",
     "dfgw.to_csv(csv_file, index=False)"
    ]
   },
@@ -397,7 +386,7 @@
     "    parameterCd=pcode, \n",
     "    multi_index=False\n",
     ")\n",
-    "df.to_csv(os.path.join(data_path, \"RR_gage_data.csv\"))"
+    "df.to_csv(data_path / \"RR_gage_data.csv\")"
    ]
   },
   {
@@ -407,7 +396,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.read_csv(os.path.join(data_path, \"RR_gage_data.csv\"))\n",
+    "df = pd.read_csv(data_path / \"RR_gage_data.csv\", dtype={'site_no': object})\n",
     "df[\"datetime\"] = pd.to_datetime(df[\"datetime\"])\n",
     "df = df.set_index(\"datetime\")\n",
     "df.head()"
@@ -501,6 +490,16 @@
     "the `rename()` method accepts a dictionary that is formated `{current_col_name: new_col_name}`"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e79003ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "info"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -648,7 +647,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "cimis_file = os.path.join(data_path, \"santa_rosa_CIMIS_83.csv\")\n",
+    "cimis_file = data_path / \"santa_rosa_CIMIS_83.csv\"\n",
     "df_cimis = pd.read_csv(cimis_file)\n",
     "drop_list = [\"qc\"] + [f\"qc.{i}\" for i in range(1, 22)]\n",
     "df_cimis.drop(columns=drop_list, inplace=True)\n",
@@ -1108,7 +1107,7 @@
     "# add the decomposition trend to the dataframe to make plotting easy\n",
     "df2[\"baseflow_trend\"] = decomposition.trend\n",
     "\n",
-    "pdf_file = os.path.join(data_path, \"all_years_russian.pdf\")\n",
+    "pdf_file = data_path / \"all_years_russian.pdf\"\n",
     "with PdfPages(pdf_file) as outpdf:\n",
     "    for year in sorted(df2.year.unique()):\n",
     "        plt.figure()\n",