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-rw-r--r--bjoern/videoanalyse/tab_switch.py48
1 files changed, 48 insertions, 0 deletions
diff --git a/bjoern/videoanalyse/tab_switch.py b/bjoern/videoanalyse/tab_switch.py
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+++ b/bjoern/videoanalyse/tab_switch.py
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+#!/usr/bin/env python3
+
+import pandas as pd
+
+
+def tab_switches_per_type(df):
+ # url_types = ["url", "log_url", "longest", "most_frequent"]
+ # dist_types = [
+ # "levenshtein-distance",
+ # "levenshtein-distance",
+ # "longest-distance",
+ # "most_frequent-distance",
+ # ]
+
+ result = {
+ "vp_code": [],
+ "log_url": [],
+ "count": [],
+ "group": [],
+ "longest_url": [],
+ "longest-distance": [],
+ "most_frequent_url": [],
+ "most_frequent-distance": [],
+ }
+ last_group = -1
+ count = -1
+ for row in df.iterrows():
+ row = row[1]
+ if row["group_index"] != last_group:
+ result["vp_code"].append(row["vp_code"])
+ result["group"].append(row["group_index"])
+ result["log_url"].append(row["log_url"])
+ result["longest_url"].append(row["longest"])
+ result["longest-distance"].append(row["longest-distance"])
+ result["most_frequent_url"].append(row["most_frequent"])
+ result["most_frequent-distance"].append(row["most_frequent-distance"])
+
+ last_group = row["group_index"]
+ if count == -1:
+ count = 1
+ continue
+ result["count"].append(count)
+ count = 1
+ else:
+ count += 1
+ result["count"].append(count)
+ result_df = pd.DataFrame(result)
+ return result_df