https://heidelsec.de/de/tags/python/Recent content in Python on HeidelSechttps://heidelsec.de/images/og.jpghttps://heidelsec.de/images/og.jpgHugo -- 0.167.0de2026 Datenschutzerklärung - ImpressumSat, 21 Feb 2026 09:00:00 +0100https://heidelsec.de/de/posts/2026-02-21-pandas-excel-statistiken/Sat, 21 Feb 2026 09:00:00 +0100https://heidelsec.de/de/posts/2026-02-21-pandas-excel-statistiken/<h2 id="warum-pandas-statt-excel-formeln">Warum Pandas statt Excel-Formeln?</h2> <p>Excel ist für einfache Tabellen ideal, aber bei größeren Datenmengen wird&rsquo;s schnell unübersichtlich. Mit <strong>Pandas</strong> lassen sich Excel-Dateien einlesen, analysieren und statistisch auswerten – reproduzierbar und automatisierbar.</p> <hr> <h2 id="installation">Installation</h2> <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-bash" data-lang="bash"><span class="line"><span class="cl">pip install pandas openpyxl </span></span></code></pre></div><p><code>openpyxl</code> wird für Excel-Dateien (.xlsx) benötigt.</p> <hr> <h2 id="excel-datei-einlesen">Excel-Datei einlesen</h2> <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"><span class="line"><span class="cl"><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span> </span></span><span class="line"><span class="cl"> </span></span><span class="line"><span class="cl"><span class="c1"># Excel-Datei einlesen</span> </span></span><span class="line"><span class="cl"><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_excel</span><span class="p">(</span><span class="s1">&#39;verkaufsdaten.xlsx&#39;</span><span class="p">,</span> <span class="n">sheet_name</span><span class="o">=</span><span class="s1">&#39;Umsätze&#39;</span><span class="p">)</span> </span></span><span class="line"><span class="cl"> </span></span><span class="line"><span class="cl"><span class="c1"># Ersten Blick auf die Daten</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">())</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">info</span><span class="p">())</span> </span></span></code></pre></div><p><strong>Wichtige Parameter:</strong></p> <ul> <li><code>sheet_name='Name'</code> – Bestimmtes Tabellenblatt auswählen</li> <li><code>usecols='A:E'</code> – Nur bestimmte Spalten einlesen</li> <li><code>skiprows=2</code> – Erste Zeilen überspringen</li> </ul> <hr> <h2 id="basis-statistiken">Basis-Statistiken</h2> <div class="highlight"><pre tabindex="0" class="chroma"><code class="language-python" data-lang="python"><span class="line"><span class="cl"><span class="c1"># Schneller Überblick</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">describe</span><span class="p">())</span> </span></span><span class="line"><span class="cl"> </span></span><span class="line"><span class="cl"><span class="c1"># Einzelne Statistiken</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&#34;Durchschnitt: </span><span class="si">{</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Umsatz&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">mean</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> €&#34;</span><span class="p">)</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&#34;Median: </span><span class="si">{</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Umsatz&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> €&#34;</span><span class="p">)</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&#34;Minimum: </span><span class="si">{</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Umsatz&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">min</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> €&#34;</span><span class="p">)</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&#34;Maximum: </span><span class="si">{</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Umsatz&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">max</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> €&#34;</span><span class="p">)</span> </span></span><span class="line"><span class="cl"><span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s2">&#34;Summe: </span><span class="si">{</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;Umsatz&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="si">:</span><span class="s2">.2f</span><span class="si">}</span><span class="s2"> €&#34;</span><span class="p">)</span> </span></span></code></pre></div><p><strong>Output:</strong></p>