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Timeline_Matplotlib.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# In[99]:
+
+
+import matplotlib.pyplot as plt
+import numpy as np
+import matplotlib.dates as mdates
+from matplotlib.pyplot import figure
+import pandas as pd
+
+# https://gitlab.rlp.net/-/profile/personal_access_tokens
+
+try:
+    # Fetch JSON data
+
+    import urllib.request
+    import json
+
+    url = "https://raw.githubusercontent.com/MonikaBarget/GeoHumTutorials/master/Historische%20Karten%20Kurmainz.json"
+    data = json.loads(urllib.request.urlopen(url, timeout=.4).read().decode())
+
+    print("No. of items found: ", len(data))
+
+    dates_1650=[]
+    dates_1700=[]
+    dates_1750=[]
+    dates_1800=[]
+    dates_new =[]
+    names_1650=[]
+    names_1700=[]
+    names_1750=[]
+    names_1800=[]
+
+    for item in data:
+        date=item['issued']['date-parts']
+        #print(date)
+        date_str = date[0][0]
+        #print(date_str)
+        if int(date_str)<=1650:
+            dates_1650.append(date_str)
+            names_1650.append(item['title'][:20])
+        if 1651<=int(date_str)<=1700:
+            dates_1700.append(date_str)
+            names_1700.append(item['title'][:20])
+        if 1701<=int(date_str)<=1750:
+            dates_1750.append(date_str)
+            names_1750.append(item['title'][:20])
+        if 1751<int(date_str)<=1800:
+            dates_1800.append(date_str)
+            names_1800.append(item['title'][:20])
+
+    print("Number of items to be plotted: ", len(dates))
+
+except ValueError:
+    print("no data")
+
+# split large data sets into several graphs
+
+print(dates_1650)
+print(names_1650)
+time_range=[dates_1650, dates_1700, dates_1750, dates_1800]
+name_range=[names_1650, names_1700, names_1750, names_1800]
+graph_num=range(0, 4)
+
+for g in graph_num:
+    print(g)
+    dates_new=time_range[g]
+    names_new=name_range[g]
+    print(names_new)
+
+    # Create plot
+
+    fig, ax = plt.subplots(figsize=(20, 20))
+    ax.set(title="Publikationsdatum")
+    ax.scatter(sorted(dates_new), names_new, c='#bcbd22', marker=5)
+
+    # Axes.scatter(self, x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, verts=<deprecated parameter>, edgecolors=None, *, plotnonfinite=False, data=None, **kwargs)
+
+    ax.set_xlabel(r'Publikationsdatum', fontsize=15)
+    ax.set_xlim(min(dates_new), max(dates_new))
+    ax.set_ylabel(r'Kartentitel', fontsize=15)
+    ax.set_title('Historische Karten zu Kurmainz')
+
+    # Highlight reproductions
+
+    df = pd.DataFrame(dates_new) 
+    duplicates=df[df.duplicated()]
+    plt.scatter(dates_new, names_new, color="red")
+
+    # Set axes details  
+
+    plt.xticks(dates_new, rotation=45, horizontalalignment='right')
+    #plt.tick_params(axis='x', colors='red', direction='out', length=13, width=7)
+    ax.tick_params(axis='both', which='major', pad=20)
+    ax.set_aspect(aspect=0.5)
+    plt.tight_layout()
+    plt.show()
+    plt.savefig("graph%s.svg" % i, dpi = 300)
+    plt.close()
+
+print("DONE")
+
+
+# In[ ]:
+
+
+
+
+
+# In[ ]:
+
+
+
+