barchart

chatanalyzer/__main__.py

@@ -14,9 +14,9 @@ def read_json(filename):
         return json.load(f)
 
 
-def main():
+def main(arguments=list(sys.argv[1:])):
     participants = []
-    file_list = list(sys.argv[1:])
+    file_list = arguments
 
     chat_data = read_json(file_list[0])
 
@@ -36,15 +36,19 @@ def main():
     
     WORDS_IN_CHAT = count_all_words(participants)
     for p in participants:
+        print(p.name)
         p.count_words()
 
     print("The participants of this chat:")
     for p in participants:
         print(f"{p.name}\n")
+    
+    # print(participants[0].message_count)
 
     analyzing.make_wordcloud(WORDS_IN_CHAT)
-    # analyzing.make_timeline(participants)
+    analyzing.make_timeline(participants)
-    # make_final.assemble_image(participants)
+    analyzing.make_barchart(participants, WORDS_IN_CHAT)
+    make_final.assemble_image(participants)
 
 
 if __name__ == "__main__":

chatanalyzer/analyzing.py

@@ -23,6 +23,11 @@ def incidents_of_words(words):
     return d
 
 
+def set_sender(s, p):
+    s = p.name
+    return s
+
+
 def create_dataframe(participants):
     skeleton = {"month": [],
                 "counts": [],
@@ -90,3 +95,51 @@ def make_timeline(participants):
                         })
 
     fig.write_image(f"{RESOURCE_LOCATION}/timeline.png",format="png", width=1500, height=600, scale=3)
+
+
+def make_barchart(participants, WORDS_IN_CHAT):
+    words = {}
+    df = pd.DataFrame({"sender": [], "message": [], "counts": []})
+    
+    for key in list(clean_text(WORDS_IN_CHAT, HUNGARIAN_STOPWORDS).keys())[:50]:
+        # print(key, WORDS_IN_CHAT[key])
+        words[key] = WORDS_IN_CHAT[key]
+    
+    for p in participants:
+        df_c = pd.DataFrame({"message": [], "counts": [], "sender": []})
+        df_p = p.words.loc[p.words['message'].isin(list(words.keys()))]
+
+        words_count = df_p['message'].value_counts().sort_index()
+        df_c = words_count.rename_axis('message').reset_index(name='counts')
+        # print(df_c)
+        df_c['sender'] = p.name#df_c.apply(lambda row : set_sender(row['sender'], p), axis = 1)
+
+        df = pd.concat([df, df_c], ignore_index=True)
+        # print(df_c)
+        # sender=[]
+        # sender += [p.name]*df.count()
+        # df["sender"] = sender
+    
+    fig = px.bar(df, x="counts", y="message", color="sender", orientation='h', height=5000)
+    fig.update_layout({ "showlegend": False,
+                        "bargap": 0.5,
+                        "title": {"text": "MOST USED WORDS",
+                                "x": 0.5,
+                                "font": {"color": "white"}},
+                        "xaxis": {"showgrid": False,
+                                    "title": "",
+                                    "nticks": 5,
+                                    "color": "white"},
+                        "yaxis": {"color": "white",
+                                    "nticks": 50,
+                                    "categoryorder": "sum ascending",
+                                    "title": {"text": ""},
+                                    "color": "white"},
+                        "paper_bgcolor": 'rgba(255,255,255,0)',
+                        "plot_bgcolor": 'rgba(255,255,255,0)'
+                        })
+ 
+    fig.write_image(f"{RESOURCE_LOCATION}/barchart.png",format="png", width=500, height=1200, scale=3)
+    
+    # df = pd.DataFrame({"message": list(words.keys())})
+    # print(df)

chatanalyzer/make_final.py

@@ -28,7 +28,7 @@ def generate_images_from_text(x, y, txt):
     return img
 
 
-def assemble_image(participants, wordcloudimg="wordcloud.png", timelineimg="timeline.png"):
+def assemble_image(participants, wordcloudimg="wordcloud.png", timelineimg="timeline.png", barchartimg="barchart.png"):
     if participants[0].chat_type == "Regular":
         names = []
         for p in participants:
@@ -42,21 +42,24 @@ def assemble_image(participants, wordcloudimg="wordcloud.png", timelineimg="time
 
     number_of_messages = 0
     for p in participants:
-        number_of_messages += len(p.messages)
+        number_of_messages += p.message_count
     
     n_o_m = generate_images_from_text(750, 350, str(number_of_messages))
     # n_o_m.save(f'{RESOURCE_LOCATION}/number_of_messages.png')
     n_o_m_text = generate_images_from_text(750, 400, "TOTAL NUMBER OF MESSAGES")
     # n_o_m_text.save(f'{RESOURCE_LOCATION}/number_of_messages_text.png')
 
-    final = Image.new('RGB', (5000, 8000), (0, 0, 0))
+    final = Image.new('RGBA', (5000, 8000), (35, 35, 35, 255))
-    final.paste(names, (0, 0))
+    final.paste(names, (0, 0),mask=names)
-    final.paste(n_o_m_text, (3250, 4400))
+    final.paste(n_o_m_text, (3250, 4400), mask=n_o_m_text)
-    final.paste(n_o_m, (3250, 4750))
+    final.paste(n_o_m, (3250, 4750), mask=n_o_m)
     wordcloud = Image.open(f"{RESOURCE_LOCATION}/{wordcloudimg}")
-    final.paste(wordcloud, (1500, 600))
+    # alpha = wordcloud.convert('RGBA').split()[-1]
+    final.paste(wordcloud, (1500, 600), mask=wordcloud)
     timeline = Image.open(f"{RESOURCE_LOCATION}/{timelineimg}")
-    final.paste(timeline, (250, 2600))
+    final.paste(timeline, (250, 2600), mask=timeline)
+    barchart = Image.open(f"{RESOURCE_LOCATION}/{barchartimg}")
+    final.paste(barchart, (1750, 4400),  mask=barchart)
 
 
     final.save(f"{RESOURCE_LOCATION}/final.png")

chatanalyzer/participant.py

@@ -19,7 +19,12 @@ def count_all_words(participants):
     words_count = words['message'].value_counts().sort_index()
     df_out = words_count.rename_axis('message').reset_index(name='counts')
     df_out['message'] = df_out.apply(lambda row : to_uppercase(row['message']), axis = 1)
-    return df_out.sort_values(by="counts", ascending=True).set_index("message").to_dict()["counts"]
+    # print(df_out.sort_values(by="counts", ascending=True).set_index("message"))
+    d = df_out.sort_values(by="counts", ascending=True).set_index("message").to_dict()["counts"]
+    marklist = sorted(d.items(), key=lambda x:x[1], reverse=True)
+    sortdict = dict(marklist)
+    # print(sortdict)
+    return sortdict
 
 class Participant:
     def __init__(self, name, title, chat_type):
@@ -29,14 +34,17 @@ class Participant:
         self.chat_type = chat_type
         self.messages_df = pd.DataFrame({"timestamp": [], "message": []})
         self.words = pd.DataFrame()
+        self.message_count = 0
     
     def add_message(self, timestamp, message):
         self.messages_df = self.messages_df.append(dict(zip(self.messages_df.columns,[str(datetime.fromtimestamp(timestamp/1000)), ftfy.ftfy(message)])), ignore_index=True)
     
     def count_words(self):
         words = self.messages_df.set_index(['timestamp']).apply(lambda x: x.str.split(' ').explode()).reset_index()
-        words_count = words['message'].value_counts().sort_index()
+        # words_count = words['message'].value_counts().sort_index()
-        self.words = words_count.rename_axis('message').reset_index(name='counts')
+        words['message'] = words.apply(lambda row : to_uppercase(row['message']), axis = 1)
+        self.words = words.rename_axis('message')#.reset_index(name='counts')
+        self.message_count = self.messages_df.count()[0]
     
     def get_words(self, longer_than=0):
         words = []