{"cells":[{"cell_type":"markdown","source":["# Import Packages\n"],"metadata":{"id":"aUpT5dNsWm42"}},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":32276,"status":"ok","timestamp":1703061225405,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"W3lZ459Kq9SZ","outputId":"6ef28bfb-cdc2-49db-d69d-9edc8a5bffb4"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting kaleido\n"," Downloading kaleido-0.2.1-py2.py3-none-manylinux1_x86_64.whl (79.9 MB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.9/79.9 MB\u001b[0m \u001b[31m8.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hInstalling collected packages: kaleido\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","lida 0.0.10 requires fastapi, which is not installed.\n","lida 0.0.10 requires python-multipart, which is not installed.\n","lida 0.0.10 requires uvicorn, which is not installed.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed kaleido-0.2.1\n"]}],"source":["%pip install -U kaleido"]},{"cell_type":"code","execution_count":2,"metadata":{"id":"OnxNBILOSWU0","executionInfo":{"status":"ok","timestamp":1703061229157,"user_tz":-60,"elapsed":3760,"user":{"displayName":"M. V.","userId":"14299655237261780537"}}},"outputs":[],"source":["#Import requiered Packages\n","\n","#Python Versio 3.8.5.\n","import numpy as np # version 1.24.4\n","import pandas as pd # version 2.0.3\n","import matplotlib.pyplot as plt # version 3.6.0\n","import array\n","import math\n","import os\n","import kaleido\n","import glob\n","import plotly.express as px # version 5.10.0\n","from plotly.subplots import make_subplots\n","import plotly.graph_objects as go\n","import textwrap\n","import itertools as it\n","import statsmodels # version 0.13.5\n","import statsmodels.formula.api as smf\n","import statsmodels.api as sm\n","from statsmodels.formula.api import ols\n","from sklearn.linear_model import LinearRegression\n","import scipy.stats as stats\n","from statsmodels.stats.multicomp import pairwise_tukeyhsd\n","from scipy.stats import mannwhitneyu\n","from scipy.stats import spearmanr"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2253,"status":"ok","timestamp":1703061966156,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"bIEqKRGVTUNw","outputId":"75c3ba17-d04e-4054-848a-44a3fb6f05df"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["#Import of Data\n","from google.colab import drive\n","drive.mount('/content/drive')\n","df = pd.read_csv(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/LCWissDD-df_vereinfacht_short.csv\")"]},{"cell_type":"code","execution_count":7,"metadata":{"id":"2FI5QwhKSWU2","executionInfo":{"status":"ok","timestamp":1703061968640,"user_tz":-60,"elapsed":252,"user":{"displayName":"M. V.","userId":"14299655237261780537"}}},"outputs":[],"source":["#split data in groups for every Academic Year!\n","df1 = df.loc[df['Fachsemester'].isin([1,2])]\n","df2 = df.loc[df['Fachsemester'].isin([3,4])]\n","df3 = df.loc[df['Fachsemester'].isin([5,6])]\n","df4 = df.loc[df['Fachsemester'].isin([7,8])]\n","df5 = df.loc[df['Fachsemester'].isin([9,10])]\n"]},{"cell_type":"markdown","metadata":{"id":"T5l6T7r8SWU2"},"source":["# Plotting figures\n","----------------\n","\n"]},{"cell_type":"markdown","source":["## Figure 1 - Relevance 5AY"],"metadata":{"id":"6xVGb5l5XVuB"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":617},"executionInfo":{"elapsed":971,"status":"ok","timestamp":1700772869644,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"oM6eatdhSWU3","outputId":"8704936e-7589-4a57-b6ad-ca2db6b46a40"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#horizontal StackedBarplot für Berufserwartung 5.Studienjahr\n","\n","#Berechnen der relativen Antworten für E030 - Items (1=working with lit, 2=work on research project ,3=comprehend guideline ,4=explaining)\n","show1 = df5[\"ErwartungLiteratur\"].value_counts(normalize=True, dropna=False) * 100\n","show2 = df5[\"ErwartungForschungsprojk\"].value_counts(normalize=True, dropna=False) * 100\n","show4 = df5[\"ErwartungEvidenzNachvoll\"].value_counts(normalize=True, dropna=False) * 100\n","show8 = df5[\"ErwartungPatientenErkl\"].value_counts(normalize=True, dropna=False) * 100\n","showUlt = pd.concat([show8, show4, show1, show2], axis=1)\n","showUlt = showUlt.transpose()\n","\n","#Umbenennen der Abgefragte Items ins english\n","husten = ['explain scientific findings
(on diagnostics, therapy, etc.)
to patients','comprehend evidence
of a guideline',\n"," 'work with scientific literature','work on a research project',]\n","\n","#Auftragen jeder Antwortmöglichkeit für jedes Studienjahr\n","fig = go.Figure()\n","fig.add_trace(go.Bar(x=showUlt[4], name=\"daily\", y=husten, orientation='h',\n"," text=showUlt[4].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=6,\n"," marker=dict(line=dict(width=1), color=\"#03425c\")))\n","fig.add_trace(go.Bar(x=showUlt[3.0], name=\"weekly\", y=husten, orientation='h',\n"," text=showUlt[3].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=5,\n"," marker=dict(line=dict(width=1), color=\"#004F70 \")))\n","fig.add_trace(go.Bar(x=showUlt[2.0], name=\"monthly\", y=husten, orientation='h',\n"," text=showUlt[2].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=4,\n"," marker=dict(line=dict(width=1), color=\"#006AB3\")))\n","fig.add_trace(go.Bar(x=showUlt[1.0], name=\"rarely\", y=husten, orientation='h',\n"," text=showUlt[1].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=3,\n"," marker=dict(line=dict(width=1), color=\"#38AEFF\")))\n","fig.add_trace(go.Bar(x=showUlt[0.0], name=\"never\", y=husten, orientation='h',\n"," text=showUlt[0].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=2,\n"," marker=dict(line=dict(width=1), color=\"#7BC9FF \")))\n","fig.add_trace(go.Bar(x=showUlt[np.nan], name=\"no statement possible\", y=husten, orientation='h',\n"," text=showUlt[np.nan].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\",\n"," textangle=270, legendrank=1,\n"," marker=dict(line=dict(width=1), color=\"#BDE4FF \")))\n","\n","fig.update_layout(shapes=[\n"," dict(\n"," type='line',\n"," x0=50,\n"," y0=-0.5,\n"," x1=50,\n"," y1=len(husten)-0.5,\n"," line=dict(\n"," color='black',\n"," width=1.5,\n"," dash='dash'\n"," )\n"," )\n","],\n","barmode='stack', template=\"simple_white\",\n"," title=\"How often does the 5th year student expect in the later profession to ...\",\n"," yaxis=dict(title=\"Statement\", title_font=dict( size=18,),tickfont=dict(size=14,),),\n"," xaxis=dict(title=\"% of participants\", tickmode='linear', dtick=10, range=[0, 100], title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," legend=dict(title=\"\"),\n"," height=600, width=1000,\n"," title_x=0.5,)\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E030_SQ001.svg\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E030_SQ001.png\")\n","\n"]},{"cell_type":"markdown","source":["## Figure 2 - Satisfaction"],"metadata":{"id":"rYI7DtTxXbZD"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":617},"executionInfo":{"elapsed":1477,"status":"ok","timestamp":1700772859913,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"o8aWj3yTSWU5","outputId":"31f2e379-c3a3-4dcb-9e98-c1b73e7be89a"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#Aussagen: Ich bin zufrieden mit W.Curriculum an meiner Fakultät für alle Jahrgänge - horizontal stacked Barplot\n","show1 = df5[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","show2 = df4[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","show3 = df3[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","show4 = df2[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","show5 = df1[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","showUlt = pd.concat([show1, show2, show3, show4, show5], axis=1)\n","showUlt =showUlt.transpose()\n","husten=['5','4', '3', '2', '1' ]\n","\n","\n","fig = go.Figure()\n","fig.add_trace(go.Bar(x=showUlt[5], name=\"1 - fully agree\", y=husten, orientation='h',\n"," text=showUlt[5].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=6,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#03425c\")))\n","fig.add_trace(go.Bar(x=showUlt[4], name=\"2 - rather agree\", y=husten, orientation='h',\n"," text=showUlt[4].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=5,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#004F70\")))\n","fig.add_trace(go.Bar(x=showUlt[3], name=\"3 - partially\", y=husten, orientation='h',\n"," text=showUlt[3].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=4,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#006AB3\")))\n","fig.add_trace(go.Bar(x=showUlt[2], name=\"4 - rather disagree\", y=husten, orientation='h',\n"," text=showUlt[2].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=3,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#38AEFF\")))\n","fig.add_trace(go.Bar(x=showUlt[1], name=\"5 - completely disagree\", y=husten, orientation='h',\n"," text=showUlt[1].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=2,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#7BC9FF\")))\n","fig.add_trace(go.Bar(x=showUlt[0], name=\"no statement possible\", y=husten, orientation='h',\n"," text=showUlt[0].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=1,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#BDE4FF \")))\n","\n","fig.update_layout(shapes=[\n"," dict(\n"," type='line',\n"," x0=50,\n"," y0=-0.5,\n"," x1=50,\n"," y1=len(husten)-0.5,\n"," line=dict(\n"," color='black',\n"," width=1.5,\n"," dash='dash'\n"," )\n"," )\n","],barmode='stack', template=\"simple_white\",\n"," title=\"Statement: I am satisfied with the teaching of science skills at my faculty.\",\n"," yaxis=dict(title=\"Academic year\", title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," xaxis=dict(title=\"% of participants\", tickmode='linear', dtick=10, range=[0, 100], title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," legend=dict(title=\"\"),\n"," height=600, width=1000,\n"," title_x=0.5,)\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ002.svg\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ002.png\")"]},{"cell_type":"markdown","source":["## Figure 3 - science-Curriculum"],"metadata":{"id":"90SpQzNnXmZ7"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":617},"executionInfo":{"elapsed":1192,"status":"ok","timestamp":1700772881181,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"Io2CwokkSWU5","outputId":"5fe45366-e632-4a78-e123-db3add0d7a73"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#Aussagen: Ich möchte wiss.Arbeiten im Pflichtcurriculum vermittelt bekommen für alle Jahrgänge - horizontal stacked Barplot\n","show1 = df5[\"VermittlungWikomp\"].value_counts(normalize=True) * 100\n","show1 = df5[\"wiArbeitenPflichtcurr\"].value_counts(normalize=True) * 100\n","show2 = df4[\"wiArbeitenPflichtcurr\"].value_counts(normalize=True) * 100\n","show3 = df3[\"wiArbeitenPflichtcurr\"].value_counts(normalize=True) * 100\n","show4 = df2[\"wiArbeitenPflichtcurr\"].value_counts(normalize=True) * 100\n","show5 = df1[\"wiArbeitenPflichtcurr\"].value_counts(normalize=True) * 100\n","showUlt = pd.concat([show1, show2, show3, show4, show5], axis=1)\n","showUlt =showUlt.transpose()\n","husten=['5','4', '3', '2', '1' ]\n","\n","\n","fig = go.Figure()\n","fig.add_trace(go.Bar(x=showUlt[5], name=\"1 - fully agree\", y=husten, orientation='h',\n"," text=showUlt[5].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=6,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#03425c\")))\n","fig.add_trace(go.Bar(x=showUlt[4], name=\"2 - rather agree\", y=husten, orientation='h',\n"," text=showUlt[4].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=5,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#004F70\")))\n","fig.add_trace(go.Bar(x=showUlt[3], name=\"3 - partly/partly\", y=husten, orientation='h',\n"," text=showUlt[3].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=4,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#006AB3\")))\n","fig.add_trace(go.Bar(x=showUlt[2], name=\"4 - rather disagree\", y=husten, orientation='h',\n"," text=showUlt[2].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=3,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#38AEFF\")))\n","fig.add_trace(go.Bar(x=showUlt[1], name=\"5 - completely disagree\", y=husten, orientation='h',\n"," text=showUlt[1].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=2,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#7BC9FF\")))\n","fig.add_trace(go.Bar(x=showUlt[0], name=\"no statement possible\", y=husten, orientation='h',\n"," text=showUlt[0].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=1,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#BDE4FF \")))\n","\n","fig.update_layout(shapes=[\n"," dict(\n"," type='line',\n"," x0=50,\n"," y0=-0.5,\n"," x1=50,\n"," y1=len(husten)-0.5,\n"," line=dict(\n"," color='black',\n"," width=1.5,\n"," dash='dash'\n"," )\n"," )\n","], barmode='stack', template=\"simple_white\",\n"," title=\"Statement: I would like to have scientific work included in the compulsory curriculum.\",\n"," yaxis=dict(title=\"Academic year\", title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," xaxis=dict(title=\"% of participants\", tickmode='linear', dtick=10, range=[0, 100],title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," legend=dict(title=\"\"),\n"," height=600, width=1000,\n"," title_x=0.5,)\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ001.png\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ001.svg\")"]},{"cell_type":"markdown","source":["## Figure 4 - Doctorade - Influcence"],"metadata":{"id":"Hhn-sjv8XvAI"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":817},"executionInfo":{"elapsed":3787,"status":"ok","timestamp":1699020899789,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"iZjT-JKUSWU6","outputId":"5e7d64d2-d2e0-47d4-ff66-36b396f69e87"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#Histogramm für Einfluss Promotion auf späteren Beruf\n","\n","# Spaltennamen angepasst\n","columns = ['EinflPatVersorg', 'EinflKarrier', 'EinflGehalt', 'EinflSozAns']\n","titles = ['Influence of a doctoral thesis on
the quality of patient care',\n"," 'Influence of a doctoral thesis on
the career',\n"," 'Influence of a doctoral thesis on
the salary',\n"," 'Influence of a doctoral thesis on
the social reputation']\n","\n","# Erstellen der Subplots\n","fig = make_subplots(rows=2, cols=2, subplot_titles=titles)\n","\n","# Schleife über die Spalten\n","for i, column in enumerate(columns):\n"," # Daten für die aktuelle Spalte\n"," data = df[df[\"PromotionStand\"] != \"begonnen\"][column]\n"," dataPromo = df[df[\"PromotionStand\"] == \"begonnen\"][column]\n","\n"," # Histogramm hinzufügen\n"," fig.add_trace(\n"," go.Histogram(\n"," x=data,\n"," xbins=dict(start=0.01, end=10, size=2),\n"," name=\"Student without started doctorate\",\n"," opacity=0.5,\n"," histnorm='percent',\n"," marker_color=\"#1245ff\",\n"," showlegend=(i == 0)\n"," ),\n"," row=(i // 2) + 1,\n"," col=(i % 2) + 1\n"," )\n","\n"," fig.add_trace(\n"," go.Histogram(\n"," x=dataPromo,\n"," xbins=dict(start=0.01, end=10, size=2),\n"," name=\"Student with started doctorate\",\n"," opacity=0.5,\n"," histnorm='percent',\n"," marker_color=\"#bf8704\",\n"," showlegend=(i == 0)\n"," ),\n"," row=(i // 2) + 1,\n"," col=(i % 2) + 1\n"," )\n","\n","# Layout anpassen\n","fig.update_layout(\n"," bargap=0.2, # gap between bars of adjacent location coordinates\n"," bargroupgap=0.1, # gap between bars of the same location coordinates\n"," xaxis_range=[0, 10],\n"," width=1000,\n"," height=800,\n"," template=\"simple_white\",\n"," legend=dict(\n"," x=1.05, # Positioniert die Legende ganz rechts\n"," y=-0.2, # Positioniert die Legende ganz unten\n"," xanchor='right', # Legendenanker rechts\n"," yanchor='bottom', # Legendenanker unten\n"," font=dict( size=16,),\n"," )\n",")\n","\n","# Update xaxis properties\n","fig.update_xaxes(title_text=\"agreement of influence in points\", row=1, col=1)\n","fig.update_xaxes(title_text=\"agreement of influence in points\", row=2, col=1)\n","fig.update_xaxes(title_text=\"agreement of influence in points\", row=1, col=2)\n","fig.update_xaxes(title_text=\"agreement of influence in points\", row=2, col=2)\n","fig.update_yaxes(title_text=\"Proportion of
students in %\", range=[0, 65], dtick=10, row=1, col=1)\n","fig.update_yaxes(title_text=\"Proportion of
students in %\", range=[0, 65], dtick=10, row=1, col=2)\n","fig.update_yaxes(title_text=\"Proportion of
students in %\", range=[0, 65], dtick=10, row=2, col=1)\n","fig.update_yaxes(title_text=\"Proportion of
students in %\", range=[0, 65], dtick=10, row=2, col=2)\n","\n","\n","# x-Achse nur aller 2 aufteilen\n","fig.update_xaxes(dtick=2)\n","\n","# Diagramm anzeigen\n","fig.show()\n","\n","# Diagramm als HTML speichern\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/z030_subplot.png\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/z030_subplot.svg\")"]},{"cell_type":"markdown","source":["## Figure 5 - Assessments over AY"],"metadata":{"id":"g8YgXLp4ZsCB"}},{"cell_type":"code","source":["# Positionen für die Boxen\n","positions_object = np.arange(1, 6) - 0\n","positions_subject = np.arange(1, 6) + 0.35\n","\n","# Erstellen Sie ein Subplot mit zwei Y-Achsen\n","fig = make_subplots(specs=[[{\"secondary_y\": True}]])\n","\n","# Fügen Sie die Traces für die objectAssessment-Daten hinzu\n","for i, df in enumerate([df1, df2, df3, df4, df5]):\n"," fig.add_trace(go.Box(y=df[\"objectAssessment\"], line_color='#006AB3', name=\"{}.\".format(i+1), x=[positions_object[i]]*len(df)), secondary_y=False)\n","\n","# Fügen Sie die Traces für die subjectAssessment-Daten hinzu\n","for i, df in enumerate([df1, df2, df3, df4, df5]):\n"," fig.add_trace(go.Box(y=df[\"subjectAssesment\"], line_color='#38AEFF', name=\"{}.\".format(i+1), x=[positions_subject[i]]*len(df)), secondary_y=True)\n","\n","# Aktualisieren Sie das Layout\n","fig.update_layout(\n"," showlegend=False,\n"," template=\"simple_white\",\n"," #title=\"Objectiv-assessment and Self-assessment Scores\",\n"," title_x=0.5,\n"," xaxis=dict(\n"," tickmode='array',\n"," tickvals=positions_object,\n"," ticktext=['1.', '2.', '3.', '4.', '5.']\n"," )\n",")\n","\n","# Aktualisieren Sie die X-Achse\n","fig.update_xaxes(title_text='Academic year', tickfont=dict(size=16,), title_font=dict(size=20,))\n","\n","# Aktualisieren Sie die Y-Achsen\n","fig.update_yaxes(\n"," tickmode='linear',\n"," dtick=1,\n"," range=[-0.5, 10.5],\n"," title_text='Objectiv-assessment score',\n"," title_font=dict(size=20, color='#006AB3'),\n"," tickfont=dict(size=16, color='#006AB3'),\n"," secondary_y=False\n",")\n","fig.update_yaxes(\n"," tickmode='linear',\n"," dtick=5,\n"," range=[-0.5, 53.5],\n"," title_text='Self-assessment score',\n"," title_font=dict(size=20, color='#38AEFF'),\n"," tickfont=dict(size=16, color='#38AEFF'),\n"," secondary_y=True\n",")\n","\n","# Anzeigen\n","fig.show()\n","# Speichern\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/Combined_Box_FS.png\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":542},"id":"poGyqBEUZwEV","executionInfo":{"status":"ok","timestamp":1703061972463,"user_tz":-60,"elapsed":662,"user":{"displayName":"M. V.","userId":"14299655237261780537"}},"outputId":"77550bb7-945a-4d6d-86aa-774896b0af43"},"execution_count":8,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}]},{"cell_type":"markdown","source":["## Figure 8 a - Doctorade -SelfAssessment + Stat"],"metadata":{"id":"bpoab-f1X6Gv"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":558},"executionInfo":{"elapsed":4729,"status":"ok","timestamp":1702978907839,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"0Y8Bj3zmSWU8","outputId":"52afb71e-c2fa-4931-f867-31195f8810b0"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["t-Statistik=-7.335, p=0.000000000002\n","Median von A1: 11.5\n","Median von A2: 25.0\n","Interquartilbereich von A1: 19.25 - 5.0\n","Interquartilbereich von A2: 37.0 - 13.5\n"]}],"source":["df_filtered = df[df['Fachsemester'] > 6]\n","\n","fig = go.Figure()\n","\n","y_values_A1 = df_filtered[\"subjectAssesment\"][(df_filtered[\"PromotionStand\"] != 'begonnen')]\n","y_values_A2 = df_filtered[\"subjectAssesment\"][(df_filtered[\"PromotionStand\"] == 'begonnen')]\n","annotations = []\n","n_A2 = len(y_values_A2)\n","n_A1 = len(y_values_A1)\n","\n","fig.add_trace(go.Box(\n"," y=df_filtered[\"subjectAssesment\"][(df_filtered[\"PromotionStand\"] != 'begonnen')],\n"," line_color='black',\n"," fillcolor='#38AEFF',\n"," opacity=1,\n"," legendgroup='non doctorate',\n"," name='non doctorate',\n"," showlegend=False\n"," ))\n","\n","fig.add_trace(go.Box(\n"," y=df_filtered[\"subjectAssesment\"][(df_filtered[\"PromotionStand\"] == 'begonnen')],\n"," line_color='black',\n"," fillcolor='#006AB3',\n"," opacity=1,\n"," legendgroup='doctorate',\n"," name='doctorate',\n"," showlegend=False\n","))\n","\n"," # Add annotations\n","annotations.append(dict(x=1., y=53.5, text=f\"n={n_A2}\", font=dict(size=16), showarrow=False))\n","annotations.append(dict(x=0, y=53.5, text=f\"n={n_A1}\", font=dict(size=16),showarrow=False))\n","\n","fig.update_layout(annotations=annotations)\n","fig.update_layout(\n"," showlegend=True, template=\"simple_white\",\n"," height=450,\n"," width= 600,\n"," title_x=1,\n"," title=dict(\n"," #text=\"Self-assessment score Doctorate vs Non-Doctorate in 4th and 5th Academic Year\",\n"," x=0.5,\n"," font=dict(\n"," size=24,\n"," ),\n"," ),\n"," xaxis=dict(\n"," title_text='doctorate status',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=20,),\n"," ),\n"," yaxis=dict(\n"," dtick=5,\n"," range=[-0.5, 53.6],\n"," title_text='Self-assessment score',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=16,),\n"," ),\n"," legend=dict(\n"," x=1.2, # Horizontale Position (1 ist ganz rechts)\n"," y=0.8, # Vertikale Position (0 ist ganz unten)\n"," traceorder=\"normal\",\n"," font=dict(\n"," size=16,\n"," ),\n"," bgcolor=\"White\",\n"," bordercolor=\"Black\",\n"," borderwidth=2,\n"," xanchor='right', # 'auto', 'left', 'center' , 'right'\n"," yanchor='bottom', # 'auto', 'top', 'middle', 'bottom'\n"," )\n",")\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/SelbstKpkt_FS-Promotion.png\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/SelbstKpkt_FS-Promotion.svg\")\n","\n","# Durchführung des t-Tests\n","t_stat, p = stats.ttest_ind(y_values_A1, y_values_A2, equal_var=True)\n","\n","# Ausgabe der Ergebnisse\n","print('t-Statistik=%.3f, p=%.12f' % (t_stat, p))\n","\n","\n","print(\"Median von A1:\", np.median(y_values_A1))\n","print(\"Median von A2:\", np.median(y_values_A2))\n","print(\"Interquartilbereich von A1:\", np.percentile(y_values_A1, 75),\" - \",np.percentile(y_values_A1, 25))\n","print(\"Interquartilbereich von A2:\", np.percentile(y_values_A2, 75),\" - \",np.percentile(y_values_A2, 25))"]},{"cell_type":"markdown","source":["## Figure 8b - Eduaction on Self-Assessment + Stat"],"metadata":{"id":"rhdQWqyTYFZk"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":558},"executionInfo":{"elapsed":881,"status":"ok","timestamp":1702978933115,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"HI_iuAF3SWU8","outputId":"406792e4-20f4-469d-abfa-02913e047c4c"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["t-Statistik=2.745, p=0.006428937412\n","Median von A1: 18.5\n","Median von A2: 13.0\n","Interquartilbereich von A1: 32.0 - 9.0\n","Interquartilbereich von A2: 22.0 - 8.0\n"]}],"source":["\n","df_filtered = df[df['Fachsemester'] > 6]\n","\n","fig = go.Figure()\n","\n","y_values_A1 = df_filtered[\"subjectAssesment\"][(df_filtered[\"VorbildgKategor\"] == '0')]\n","y_values_A2 = df_filtered[\"subjectAssesment\"][(df_filtered[\"VorbildgKategor\"] == 'Medizinnahe Ausbildung')]\n","annotations = []\n","n_A2 = len(y_values_A2)\n","n_A1 = len(y_values_A1)\n","\n","fig.add_trace(go.Box(\n"," y=df_filtered[\"subjectAssesment\"][(df_filtered[\"VorbildgKategor\"] == '0')],\n"," line_color='black', fillcolor='#38AEFF', opacity=1, legendgroup='none', name='none',\n"," showlegend=False\n"," ))\n","\n","fig.add_trace(go.Box(\n"," y=df_filtered[\"subjectAssesment\"][(df_filtered[\"VorbildgKategor\"] == 'Medizinnahe Ausbildung')],\n"," line_color='black', fillcolor='#006AB3', opacity=1, legendgroup=' medical education', name='healthcare-related education',\n"," showlegend=False\n","))\n","\n"," # Add annotations\n","annotations.append(dict(x=1., y=53.5, text=f\"n={n_A2}\",font=dict(size=16), showarrow=False))\n","annotations.append(dict(x=0, y=53.5, text=f\"n={n_A1}\", font=dict(size=16),showarrow=False))\n","\n","fig.update_layout(annotations=annotations)\n","fig.update_layout(\n"," showlegend=True, template=\"simple_white\",\n"," height=450,\n"," width= 600,\n"," title_x=1,\n"," title=dict(\n"," #text=\"Self-assessment score medical education vs Non-medical education
in 4th and 5th Academic Year\",\n"," x=0.5,\n"," font=dict(\n"," size=24,\n"," ),\n"," ),\n"," xaxis=dict(\n"," title_text='educational background',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=16,),\n"," ),\n"," yaxis=dict(\n"," dtick=5,\n"," range=[-0.5, 53.6],\n"," title_text='Self-assessment score',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=16,),\n"," ),\n"," legend=dict(\n"," x=1.2, # Horizontale Position (1 ist ganz rechts)\n"," y=0.8, # Vertikale Position (0 ist ganz unten)\n"," traceorder=\"normal\",\n"," font=dict(\n"," size=16,\n"," ),\n"," bgcolor=\"White\",\n"," bordercolor=\"Black\",\n"," borderwidth=2,\n"," xanchor='right', # 'auto', 'left', 'center' , 'right'\n"," yanchor='bottom', # 'auto', 'top', 'middle', 'bottom'\n"," )\n",")\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/SelbstKpkt_FS-Vorbildung.svg\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/SelbstKpkt_FS-Vorbildung.png\")\n","\n","# Durchführung des unabhängigen t-Tests\n","t_stat, p = stats.ttest_ind(y_values_A1, y_values_A2, equal_var=True)\n","\n","# Ausgabe der Ergebnisse\n","print('t-Statistik=%.3f, p=%.12f' % (t_stat, p))\n","\n","\n","print(\"Median von A1:\", np.median(y_values_A1))\n","print(\"Median von A2:\", np.median(y_values_A2))\n","print(\"Interquartilbereich von A1:\", np.percentile(y_values_A1, 75),\" - \",np.percentile(y_values_A1, 25))\n","print(\"Interquartilbereich von A2:\", np.percentile(y_values_A2, 75),\" - \",np.percentile(y_values_A2, 25))\n"]},{"cell_type":"markdown","source":["## Figure 6 - Relevance and Perspective + Stat"],"metadata":{"id":"RSmsrX-rYW-1"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"oLdaWN4lSWU9"},"outputs":[],"source":["#Umstrukturierung des Relevanzscores in jediglich 3 Kategorien!\n","columns = ['ErwartungLiteratur','ErwartungForschungsprojk','ErwartungStatMethode','ErwartungwissAbhandlung','ErwartungPosterVortrag','ErwartungLeitlinie','ErwartungEvidenzNachvoll', 'ErwartungPatientenErkl']\n","\n","replacement = {0:0, 1:0, 2:1, 3:2, 4:2}\n","\n","for column in columns:\n"," df[column] = df[column].replace(replacement)\n","\n","#Zusammenfassen von Täglich und Wöchentlich zu 2, monatlich zu 1 und seltener als monatlich=0\n","#Summieren für alle Items zu Relevanzscore = 8*2=max.16 Pkt.\n","df[\"Relevanz\"] = df[columns].sum(axis=1)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":486},"executionInfo":{"elapsed":1189,"status":"ok","timestamp":1701010264539,"user":{"displayName":"M. V.","userId":"14299655237261780537"},"user_tz":-60},"id":"B6ldNqucSWU9","outputId":"45593a95-1a3d-46a7-b24a-d1ec586363c8"},"outputs":[{"output_type":"stream","name":"stderr","text":[":20: FutureWarning:\n","\n","iteritems is deprecated and will be removed in a future version. Use .items instead.\n","\n"]},{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#Relebanzscore für alle Studienjahre über Berufsperspektive als Boxplot\n","order = [\"Practice\", \"Hospital\", \"University Hospital\", \"Research\"]\n","translation = {\"Niederlassung\": \"Practice\", \"Klinik\": \"Hospital\", \"Universitätsklinikum\": \"University Hospital\", \"Forschung\": \"Research\"}\n","\n","\n","df['Beruf'] = df['Beruf'].replace(translation)\n","\n","df = df[df['Beruf'].isin(order)]\n","\n","fig = px.box(df, x=\"Beruf\", y=\"Relevanz\", template=\"simple_white\", category_orders={\"Beruf\": order})\n","\n","# Update the colors\n","fig.update_traces(line_color='black', fillcolor='#38AEFF')\n","\n","\n","counts = df['Beruf'].value_counts().reindex(order)\n","\n","\n","annotations = [dict(x=beruf, y=16.2, text=f'n={n}', xanchor='center', yanchor='bottom',font=dict(size=16), showarrow=False)\n"," for beruf, n in counts.iteritems()]\n","\n","fig.update_layout(\n"," showlegend=True, template=\"simple_white\",\n"," height=400,\n"," width= 750,\n"," title_x=1,\n"," title=dict(\n"," #text=\"Assessment of relevance according to work perspective\",\n"," x=0.5,\n"," font=dict(\n"," size=24,\n"," ),\n"," ),\n"," xaxis=dict(\n"," title_text='work prospects',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=16,),\n"," ),\n"," yaxis=dict(\n"," dtick=2,\n"," range=[-0.5, 16.3],\n"," title_text='relevance score',\n"," title_font=dict( size=20,),\n"," tickfont=dict(size=16,),\n"," ),\n"," annotations=annotations,\n",")\n","\n","fig.show()\n","\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/Rel-Beruf.svg\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/Rel-Beruf.png\")\n","\n"]},{"cell_type":"code","source":["group1 = df[\"Relevanz\"][df[\"Beruf\"] == 'Practice']\n","group2 = df[\"Relevanz\"][df[\"Beruf\"] == 'Hospital']\n","group3 = df[\"Relevanz\"][df[\"Beruf\"] == 'University Hospital']\n","group4 = df[\"Relevanz\"][df[\"Beruf\"] == 'Research']\n","\n","# ANOVA\n","F, p = stats.f_oneway(group1, group2, group3, group4)\n","\n","print(\"F-Wert:\", F)\n","print(\"p-Wert:\", p)\n","\n"," # Zusammenführen der Gruppen in ein Array und Erstellen eines Labels-Arrays\n","data = np.concatenate([group1, group2, group3, group4])\n","labels = ['Practice']*len(group1) + ['Hospital']*len(group2) + ['University']*len(group3) + ['Research']*len(group4)\n","\n"," # Durchführen von Tukey's HSD Test\n","tukey_result = pairwise_tukeyhsd(data, labels)\n","print(tukey_result)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"COKQEokQP57P","executionInfo":{"status":"ok","timestamp":1700771719362,"user_tz":-60,"elapsed":733,"user":{"displayName":"M. V.","userId":"14299655237261780537"}},"outputId":"5d3d9e33-d46b-4623-cf61-ea2227477b79"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["F-Wert: 43.10805471346012\n","p-Wert: 7.028785770577095e-26\n"," Multiple Comparison of Means - Tukey HSD, FWER=0.05 \n","=========================================================\n"," group1 group2 meandiff p-adj lower upper reject\n","---------------------------------------------------------\n","Hospital Practice -0.406 0.2254 -0.9538 0.1418 False\n","Hospital Research 3.3495 0.0 1.6635 5.0356 True\n","Hospital University 2.2287 0.0 1.5207 2.9367 True\n","Practice Research 3.7556 0.0 2.0856 5.4255 True\n","Practice University 2.6347 0.0 1.9659 3.3034 True\n","Research University -1.1209 0.341 -2.85 0.6083 False\n","---------------------------------------------------------\n"]}]},{"cell_type":"markdown","source":["## Supplement 4... ObjectiveAssessment"],"metadata":{"id":"Cgs5Z39iYkQC"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"XBAYmN1ESWU-","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1701008716902,"user_tz":-60,"elapsed":4501,"user":{"displayName":"M. V.","userId":"14299655237261780537"}},"outputId":"f319272f-8794-4eaa-f5f0-06b8b0e7c3c8"},"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
\n","
\n","\n",""]},"metadata":{}}],"source":["#Subplot für alle K-Aufgaben - supplementfigure\n","df_original = pd.read_csv(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/LCWissDD-df_shorter.csv\")\n","df_original['Studienjahr'] = df_original['Fachsemester'].apply(lambda x: np.ceil(x / 2))\n","df_filtered = df_original[df_original['Studienjahr'].isin(range(1, 6))]\n","# Berechne die Durchschnittswerte gruppiert nach 'Studienjahr\n","grouped = df_filtered.groupby('Studienjahr')[['W01pkt', 'W02pkt', 'W03pkt','W04pkt', 'W05pkt', 'W06pkt','W07pkt', 'W08pkt', 'W09pkt','W10pkt']].mean()\n","\n","fig = make_subplots(rows=5, cols=2, subplot_titles=('Abstract', 'Randomisation', 'Levels of evidence','Scale types', 'Citation guidelines', 'Bias','Good Scientific Practice', 'Research question and hypothesis', 'inductive research','Promotion determination'))\n","\n","# Füge die Daten für jede der drei Spalten hinzu\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W01pkt'], name='Abstract'), row=1, col=1)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W03pkt'], name='Levels of evidence'), row=2, col=1)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W05pkt'], name='Citation guidelines'), row=3, col=1)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W07pkt'], name='Good Scientific Practice'), row=4, col=1)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W09pkt'], name='inductive research'), row=5, col=1)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W02pkt'], name='Randomisation'), row=1, col=2)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W04pkt'], name='Skalentypen'), row=2, col=2)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W06pkt'], name='Bias'), row=3, col=2)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W08pkt'], name='Research question and hypothesis'), row=4, col=2)\n","fig.add_trace(go.Bar(x=grouped.index, y=grouped['W10pkt'], name='Promotion determination'), row=5, col=2)\n","\n","# Aktualisiere die Layout-Einstellungen\n","fig.update_layout(height=1300, width=800, title_text=\"Percentage of correct answers on competency test over academic year\", showlegend=False)\n","fig.update_yaxes(title=\"Propotion of students\",range=[0, 1], dtick=0.2)\n","fig.update_xaxes(title=\"academic year\", dtick=1)\n","fig.show()\n","# Speichern Sie die Figur als HTML und als Bild\n","#fig.write_html(\"image_Export/Paper_Dresden/W_Pkt-Jahr.html\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/Supplement-ObjeAssessment.png\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/Supplement-ObjeAssessment.svg\")"]},{"cell_type":"markdown","source":["## Figure 5 - SelfAssessment 5AY"],"metadata":{"id":"F5JgJVpDYrDE"}},{"cell_type":"code","source":["df_original = pd.read_csv(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/LCWissDD-df_shorter.csv\")\n","df = df_original\n","df = df[df['Fachsemester'] > 8]\n","#Aussagen: Ich bin zufrieden mit W.Curriculum an meiner Fakultät für alle Jahrgänge - horizontal stacked Barplot\n","show1 = df[\"E010[SQ012]\"].value_counts(normalize=True) * 100\n","show2 = df[\"E010[SQ009]\"].value_counts(normalize=True) * 100\n","show3 = df[\"E010[SQ003]\"].value_counts(normalize=True) * 100\n","show4 = df[\"E010[SQ002]\"].value_counts(normalize=True) * 100\n","showUlt = pd.concat([show1, show2, show3, show4], axis=1)\n","showUlt =showUlt.transpose()\n","husten=[' working on research project', '\"good scientific practice\"', ' critical literature analysis', ' literature research',]\n","\n","fig = go.Figure()\n","fig.add_trace(go.Bar(x=showUlt[4], name=\"independent performance\", y=husten, orientation='h',\n"," text=showUlt[4].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=5,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#004F70\")))\n","fig.add_trace(go.Bar(x=showUlt[3], name=\"supervised performance\", y=husten, orientation='h',\n"," text=showUlt[3].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=4,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#006AB3\")))\n","fig.add_trace(go.Bar(x=showUlt[2], name=\"can explain\", y=husten, orientation='h',\n"," text=showUlt[2].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=3,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#38AEFF\")))\n","fig.add_trace(go.Bar(x=showUlt[1], name=\"know what\", y=husten, orientation='h',\n"," text=showUlt[1].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=2,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#7BC9FF\")))\n","fig.add_trace(go.Bar(x=showUlt[0], name=\"can do nothing\", y=husten, orientation='h',\n"," text=showUlt[0].apply(lambda x: f\"{x:.1f}\"),\n"," textposition=\"inside\", legendrank=1,\n"," textangle=270,\n"," marker=dict(line=dict(width=1), color=\"#BDE4FF \")))\n","\n","# Prozentwerte für die Schraffur\n","prozentwerte = [24.6, 30.8, 16.0,40.6,]\n","\n","# Hinzufügen der Schraffur-Spuren\n","for i, wert in enumerate(prozentwerte):\n"," fig.add_trace(go.Bar(\n"," x=[wert], y=[husten[i]],\n"," base=0,\n"," orientation='h', name=\"Target reached\",\n"," marker=dict(\n"," color='rgba(0,0,0,0)', # Transparente Farbe\n"," #pattern_shape=\"/\",\n"," line_color='rgb(0,0,0,0.6)',\n"," line_width=5,\n"," ),\n"," showlegend=False\n"," ))\n","\n","for i, wert in enumerate(prozentwerte):\n"," fig.add_trace(go.Bar(\n"," x=[100 - wert], y=[husten[i]],\n"," orientation='h',\n"," base=wert, # Start der Balken bei dem Ende der ersten Schraffur\n"," marker=dict(\n"," color='rgba(0,0,0,0)', # Transparente Farbe\n"," #pattern_shape=\".\",\n"," line_color='rgb(142,73,101,0.6)',\n"," line_width=5,\n"," ),\n"," showlegend=False\n"," ))\n","\n","fig.add_trace(go.Bar(\n"," x=[None], y=[None],\n"," marker=dict(color='rgba(255,255,255,0)'), # Vollständig transparent\n"," showlegend=True,\n"," name=\"\" # Kein Name, dient nur als Platzhalter\n","))\n","\n","fig.add_trace(go.Bar(\n"," x=[None], y=[None],\n"," marker=dict(\n"," color='rgba(0,0,0,0)',\n"," #pattern_shape=\"/\",\n"," line_color='rgb(0,0,0,0.6)',\n"," line_width=5,\n"," ),\n"," name=\"reached\"\n","))\n","\n","fig.add_trace(go.Bar(\n"," x=[None], y=[None],\n"," marker=dict(\n"," color='rgba(0,0,0,0)',\n"," #pattern_shape=\".\",\n"," line_color='rgb(142,73,101,0.6)',\n"," line_width=5,\n"," ),\n"," name=\"not reached\"\n","))\n","\n","# Anpassen des Layouts, einschließlich der Legende\n","fig.update_layout(\n"," legend=dict(\n"," yanchor=\"top\",\n"," y=1, # Position der Legende anpassen, um beide Reihen einzuschließen\n"," xanchor=\"left\",\n"," x=1.05\n"," ),\n"," annotations=[\n"," dict(\n"," xref=\"paper\", yref=\"paper\",\n"," x=1.05, y=0.855,\n"," text=\"Self assessed competence:\",\n"," showarrow=False,\n"," yanchor=\"top\",\n"," xanchor=\"left\",\n"," font=dict(\n"," size=14,\n"," color=\"black\"\n"," )\n"," )\n"," ]\n",")\n","\n","fig.update_layout(shapes=[\n"," dict(\n"," type='line',\n"," x0=50,\n"," y0=-0.5,\n"," x1=50,\n"," y1=len(husten)-0.5,\n"," line=dict(\n"," color='black',\n"," width=1.5,\n"," dash='dash'\n"," )\n"," )\n","],barmode='stack', template=\"simple_white\",\n"," title=\"Self-assessment in the 5th year according to NKLM 2.0 for ...\",\n"," yaxis=dict(title=\"\", title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," xaxis=dict(title=\"% of participants\", tickmode='linear', dtick=10, range=[0, 100], title_font=dict( size=18,),tickfont=dict(size=16,),),\n"," legend=dict(title=\"Target Competence by NKLM:\"),\n"," height=600, width=1000,\n"," title_x=0.5,)\n","\n","fig.show()\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ002.svg\")\n","fig.write_image(\"/content/drive/MyDrive/Auswertung_LCWissUmfrage/image_export/Paper_Dresden/E040SQ002.png\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":617},"id":"o9C_VNIV7BYE","executionInfo":{"status":"ok","timestamp":1701082611365,"user_tz":-60,"elapsed":2246,"user":{"displayName":"M. V.","userId":"14299655237261780537"}},"outputId":"7fedf106-0d73-47c9-f958-8937438f0c24"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","\n","\n","
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