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‎kl_py_xls_nap.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/klajosw/python/blob/master/kl_py_xls_nap.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "91c57de4",
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"metadata": {
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"id": "91c57de4"
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},
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"source": [
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"---\n",
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"\n",
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"# Solplanet forras feldolgozás Python alatt\n",
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"\n",
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"\n",
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"## Használt csomagok:\n",
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"\n",
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"\n",
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"json, matplotlib, pandas\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"Python csomagok helye\n",
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"https://pypi.org\n",
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"\n",
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"\n",
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"---\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "452b0c3b",
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"metadata": {
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"scrolled": false,
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"id": "452b0c3b"
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},
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"outputs": [],
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"source": [
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"import datetime\n",
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"import pandas as pd\n",
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"import warnings\n",
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"import datetime as dt\n",
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"from matplotlib import pyplot as plt\n",
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"warnings.filterwarnings(\"ignore\")\n",
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"\n",
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"plt.rcParams['figure.figsize'] = [12, 5] ## diagram megjelenítés mértezés\n",
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"\n",
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"kl_file =r'c:\\Users\\kecskemetil\\Documents\\sj\\napelem\\solplanet_napok\\Daily Energy20230'\n",
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"\n",
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"\n",
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"kl_tartalom = pd.read_excel(kl_file +'201.xls') ## 02.01. betöltés\n",
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"## ciklus olvasás a napokra\n",
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"for i in range(202,217): ## 02.02-02.16. betöltés\n",
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" kl_file2 = kl_file + '{}.xls'.format(i)\n",
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" kl_tmp = pd.read_excel(kl_file + '{}.xls'.format(i))\n",
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" kl_tartalom = kl_tartalom.append(kl_tmp, ignore_index = True)\n",
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" \n",
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"## dátumtipusra alakítás\n",
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"kl_tartalom[\"Time\"] = pd.to_datetime(kl_tartalom[\"Time\"],format= \"%Y-%m-%d %H:%M:%S\")\n",
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" \n",
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"## dátum kiválasztás (szűrés)\n",
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"kl_tartalom.query(\"Time >= '2023-02-16 14' and Time < '2023-02-17'\", inplace = True) ## [128 rows x 5 columns]\n",
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"#kl_tartalom = kl_tartalom[(kl_tartalom['Time'] > \"2023-02-16\") & (kl_tartalom['Time'] < \"2023-02-17\")] \n",
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"#kl_tartalom = kl_tartalom[kl_tartalom['Time'].dt.strftime('%Y-%m-%d') == '2023-02-16']\n",
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"\n",
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"## felesleges mezők kihagyása\n",
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"kl_tartalom.drop(labels=['SN.','Vpv1', 'Vpv2','Ipv1','Ipv2', \n",
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"'Vac1', 'Vac2', 'Vac3', 'Iac1', 'Iac2', 'Iac3','Fac','Temp','E-Total', 'H-Total'], axis=1, inplace=True)\n",
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"\n",
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"## idő kimetszése\n",
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"#kl_tartalom[\"Time2\"] = kl_tartalom[\"Time\"].dt.time\n",
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"#kl_tartalom[\"Time2\"] = kl_tartalom[\"Time\"].dt.hour\n",
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"kl_tartalom[\"Time\"] = kl_tartalom[\"Time\"].dt.strftime('%H:%M')\n",
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" \n",
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"## mezők kiválasztása megjelenítésnél\n",
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"#print(kl_tartalom[['Time', 'Pac','E-Today']])\n",
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"\n",
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"kl_tartalom = kl_tartalom.set_index('Time')\n",
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"\n",
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"kl_tartalom['Pac'].plot(kind=\"bar\")\n",
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"plt.title(\"Napelem termelés\")\n",
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"plt.xlabel(\"Dátum\")\n",
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"plt.ylabel(\"Pac (Wh)\")\n",
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"\n",
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"#kl_tartalom.plot(kind=\"bar\")\n",
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"print(kl_tartalom)\n",
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"\n",
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"kl_tartalom.to_excel(r'c:\\Users\\kecskemetil\\Documents\\sj\\napelem\\solplanet_napok\\osszes_solplanet.xlsx', index=False, sheet_name='forras')\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0d83f70d",
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"metadata": {
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"id": "0d83f70d",
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"outputId": "8f24c8ac-913a-4ed1-e017-af6f5d446747"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"b'{\"flg\":1,\"tim\":\"20230218151822\",\"tmp\":382,\"fac\":4999,\"pac\":683,\"sac\":683,\"qac\":0,\"eto\":4420,\"etd\":197,\"hto\":185,\"pf\":83,\"wan\":0,\"err\":0,\"vac\":[2351,2350,2289],\"iac\":[11,11,11],\"vpv\":[4755,3633],\"ipv\":[83,76],\"str\":[]}'\n"
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]
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}
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],
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"source": [
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"from urllib.request import urlopen\n",
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"from bs4 import BeautifulSoup\n",
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"\n",
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"url = \"http://192.168.0.101:8484/getdevdata.cgi?device=2&sn=SP00106032280241\"\n",
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"html = urlopen(url).read()\n",
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"#soup = BeautifulSoup(html, features=\"html.parser\")\n",
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"print(html)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "992f2b7c",
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"metadata": {
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"id": "992f2b7c",
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"outputId": "13c74050-df3a-4839-cc4c-f414a0915a2f"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"A mai (2023.02.18) termelés: 20.2 KWh \n",
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"és a pillanatnyi (16:01:32 -kor) termelés: 533 Wh\n",
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"\n",
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"------------------------------------------------------------\n",
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"flg 1\n",
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"tim 20230218160132\n",
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"tmp 372\n",
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"fac 5005\n",
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"pac 533\n",
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"sac 533\n",
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"qac 0\n",
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"eto 4425\n",
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"etd 202\n",
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"hto 186\n",
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"pf 77\n",
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"wan 0\n",
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"err 0\n",
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"vac [2352, 2313, 2270]\n",
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"iac [9, 9, 10]\n",
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"vpv [4621, 3642]\n",
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"ipv [67, 59]\n",
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"str []\n"
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]
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}
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],
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"source": [
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"import urllib.request, json \n",
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"## beolvasás\n",
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"with urllib.request.urlopen(\"http://192.168.0.101:8484/getdevdata.cgi?device=2&sn=SP00106032280241\") as url:\n",
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" data = json.load(url)\n",
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"\n",
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"\n",
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"## állományba írás\n",
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"with open(r\"c:\\Users\\User\\Documents\\kl\\napelem\\kl_blog\\java\\kl_kesz_py_2023-02-18.json\", \"w\") as outfile:\n",
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" json.dump(data, outfile)\n",
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"\n",
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"## formázott megjelenítés\n",
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"print(f\"\"\"A mai ({data['tim'][0:4]}.{data['tim'][4:6]}.{data['tim'][6:8]}) termelés: {data['etd']/10:04.1f} KWh \n",
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"és a pillanatnyi ({data['tim'][8:10]}:{data['tim'][10:12]}:{data['tim'][12:14]} -kor) termelés: {data['pac']} Wh\n",
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"\"\"\")\n",
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"\n",
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"## csoportos megjelenítés\n",
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"print('-'*60)\n",
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"for key, value in data.items():\n",
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" print(key, value)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8b173d5f",
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"metadata": {
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"id": "8b173d5f"
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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},
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"colab": {
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"provenance": [],
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"include_colab_link": true
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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