plotting

1 files changed, 87 insertions, 17 deletions

diff --git a/docs/pint-pandas.ipynb b/docs/pint-pandas.ipynb
index 7b9e1ef..b4e7bc7 100644
--- a/docs/pint-pandas.ipynb
+++ b/docs/pint-pandas.ipynb
@@ -43,7 +43,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This example will show the simplist way to use pandas with pint and the underlying objects. It's slightly fiddly as you are not reading from a file. A more normal use case is given in Reading a csv.\n"
+    "This example will show the simplist way to use pandas with pint and the underlying objects. It's slightly fiddly as you are not reading from a file. A more normal use case is given in Reading a csv.\n",
+    "\n",
+    "First some imports (you don't need to import `pint_pandas` for this to work)"
    ]
   },
   {
@@ -53,8 +55,7 @@
    "outputs": [],
    "source": [
     "import pandas as pd \n",
-    "import pint\n",
-    "import pint_pandas",
+    "import pint"
    ]
   },
   {
@@ -217,12 +218,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "test_data = '''speed,mech power,torque,rail pressure,fuel flow rate,fluid power\n",
-    "rpm,kW,N m,bar,l/min,kW\n",
-    "1000.0,,10.0,1000.0,10.0,\n",
-    "1100.0,,10.0,100000000.0,10.0,\n",
-    "1200.0,,10.0,1000.0,10.0,\n",
-    "1200.0,,10.0,1000.0,10.0,'''"
+    "test_data = '''ShaftSpeedIndex,rpm,1200,1200,1200,1600,1600,1600,2300,2300,2300\n",
+    "pump,,A,B,C,A,B,C,A,B,C\n",
+    "ShaftSpeed,rpm,1200,1200,1200,1600,1600,1600,2300,2300,2300\n",
+    "FlowRate,m^3 h^-1,8.72,9.28,9.31,11.61,12.78,13.51,18.32,17.90,19.23\n",
+    "DifferentialPressure,kPa,162.03,144.16,136.47,286.86,241.41,204.21,533.17,526.74,440.76\n",
+    "ShaftPower,kW,1.32,1.23,1.18,3.09,2.78,2.50,8.59,8.51,7.61\n",
+    "Efficiency,dimensionless,30.60,31.16,30.70,30.72,31.83,31.81,32.52,31.67,32.05'''"
    ]
   },
   {
@@ -239,7 +241,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = pd.read_csv(io.StringIO(test_data), header=[0, 1])\n",
+    "df = pd.read_csv(io.StringIO(test_data), header=[0, 1], index_col = [0,1]).T\n",
     "# df = pd.read_csv(\"/path/to/test_data.csv\", header=[0, 1])\n",
     "df"
    ]
@@ -274,7 +276,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As previously, operations between DataFrame columns are unit aware"
+    "Let's confirm the units have been parsed correctly"
    ]
   },
   {
@@ -283,7 +285,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_.speed * df_.torque"
+    "df_.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here the h in m^3 h^-1 has been parsed as the planck constant. Let's change the unit to hours."
    ]
   },
   {
@@ -292,7 +301,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_"
+    "df_['FlowRate'] = pint_pandas.PintArray(df_['FlowRate'].values.quantity.m, dtype = \"pint[m^3/hr]\")\n",
+    "df_.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As previously, operations between DataFrame columns are unit aware"
    ]
   },
   {
@@ -301,8 +318,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_['mech power'] = df_.speed * df_.torque\n",
-    "df_['fluid power'] = df_['fuel flow rate'] * df_['rail pressure']\n",
+    "df_.ShaftPower / df_.ShaftSpeed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_['ShaftTorque'] = df_.ShaftPower / df_.ShaftSpeed\n",
+    "df_['FluidPower'] = df_['FlowRate'] * df_['DifferentialPressure']\n",
     "df_"
    ]
   },
@@ -335,8 +361,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_['fluid power'] = df_['fluid power'].pint.to(\"kW\")\n",
-    "df_['mech power'] = df_['mech power'].pint.to(\"kW\")\n",
+    "df_['FluidPower'] = df_['FluidPower'].pint.to(\"kW\")\n",
+    "df_['FlowRate'] = df_['FlowRate'].pint.to(\"L/s\")\n",
+    "df_['ShaftTorque'] = df_['ShaftTorque'].pint.to(\"N m\")\n",
     "df_.pint.dequantify()"
    ]
   },
@@ -377,6 +404,49 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+   "## Plotting\n",
+    "Pint's matplotlib support allows columns with the same dimensionality to be plotted."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "pint_pandas.PintType.ureg.setup_matplotlib()\n",
+    "ax = df_[['ShaftPower', 'FluidPower']].unstack(\"pump\").plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ax.yaxis.units"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that indexes cannot store PintArrays, so don't contain unit information"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(ax.xaxis.units)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "## Advanced example\n",
     "This example shows alternative ways to use pint with pandas and other features.\n",
     "\n",