diff --git a/power-stats.ipynb b/power-stats.ipynb index 60efb6849dd42c3810ecacb7488a4b09fb9add74..c2fcf36bf6d994395726c6ffe4edab9f910fcf9c 100644 --- a/power-stats.ipynb +++ b/power-stats.ipynb @@ -86,8 +86,8 @@ "metadata": {}, "outputs": [], "source": [ - "startdate = '2021/01/01 00:00:00'\n", - "enddate = '2021/04/8 00:00:00'" + "startdate = '2021/06/01 00:00:00'\n", + "enddate = '2021/10/20 00:00:00'" ] }, { @@ -96,8 +96,8 @@ "metadata": {}, "outputs": [], "source": [ - "displaystart = '2021-02-01'\n", - "displaystop = '2021-04-08'" + "displaystart = '2021-06-01'\n", + "displaystop = '2021-10-20'" ] }, { @@ -178,6 +178,15 @@ "df['datetime'] = pd.to_datetime(df.time, format=\"%Y/%m/%d %H:%M:%S\")" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -194,6 +203,51 @@ "hourly_idx=pd.date_range(startdate, enddate, freq='H')" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "hourly_idx" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "demodf=pd.DataFrame(np.zeros((1,len(hourly_idx))).T, index=hourly_idx, columns=['sum'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "demodf" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df.entity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sorted(df.entity.unique())" + ] + }, { "cell_type": "code", "execution_count": null, @@ -227,6 +281,15 @@ "m6_hourly_pwr" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "m6_hourly_pwr.fillna(0)" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -248,10 +311,59 @@ "metadata": {}, "outputs": [], "source": [ - "num_nodes=36\n", + "dftest=m6_hourly_pwr[displaystart:displaystop].fillna(0).iloc[:,1:2]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "type(dftest)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(np.__version__)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!module " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "dftest.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "startnode=35\n", + "stopnode=71\n", + "num_nodes=stopnode-startnode\n", "fig, axes = plt.subplots(num_nodes,1, sharex=True, figsize=(20,30))\n", - "for i in range(num_nodes):\n", - " m6_hourly_pwr[displaystart:displaystop].iloc[:,i+1:i+2].plot(ax=axes[i], legend=True)\n", + "for i in range(startnode, startnode+1):\n", + " print(i)\n", + " dftmp=m6_hourly_pwr[displaystart:displaystop].fillna(0).iloc[:,i+1:i+2]\n", + " dftmp.plot(ax=axes[i], legend=True)\n", " axes[i].legend(loc='lower left')" ] }, @@ -340,7 +452,7 @@ "metadata": {}, "outputs": [], "source": [ - "nan_mask = m6_hourly_pwr[\"2021-03-22\":\"2021-03-23\"].isna()" + "nan_mask = m6_hourly_pwr[startdate:enddate].isna()" ] }, { @@ -447,6 +559,15 @@ " axes[i].legend(loc='lower left')\n" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "m6_hourly_pwr.iloc[:,133:199].columns" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -465,7 +586,7 @@ "metadata": {}, "outputs": [], "source": [ - "kW = m6_hourly_pwr[displaystart:displaystop].sum(axis=1)/1000" + "kW = m6_hourly_pwr.iloc[:,133:199][displaystart:displaystop].sum(axis=1)/1000" ] }, {