start visualizations

code/myriad/loam_paper/visualization/script.py

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+import json
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+repos_info = pd.read_json("../dataset/repos_info.json")
+all_loggedin_contributors = pd.read_json("../dataset/all_loggedin_contributors.json")
+
+with open("../dataset/categories_info.json", "r") as f:
+	categories_info = json.load(f)
+
+def avg_contributors_per_category_barplot():
+    # average number of anon/loggedin contributors per category
+    data = []
+    for cat_info in categories_info:
+        category = cat_info["category"]
+        repos = repos_info.loc[repos_info["category"] == category]
+        avg_anonymous = repos.loc[:, "anonymous_contributors"].mean()
+        avg_loggedin = repos.loc[:, "loggedin_contributors"].mean()
+        if avg_anonymous == avg_anonymous: data.append(
+            {
+                "category": category, 
+                "avg_anonymous": avg_anonymous, 
+                "avg_loggedin": avg_loggedin
+            }
+        )
+    data = pd.DataFrame(data)
+    data.set_index("category").plot(kind="bar", stacked=False, color=["steelblue", "red"])
+    plt.yscale("log")
+    plt.show()
+
+def contributions_years_scatterplot():
+    # relationship between date created and number of contributions
+    g = sns.relplot(
+        data=repos_info,
+        x="created_at", y="total_contributions",
+        hue="category", size=10,
+        #legend=False,
+        #palette=cmap, sizes=(10, 200),
+    )
+    #left=0.05, right=0.55
+    #sns.move_legend(g, "lower center", bbox_to_anchor=(1, 1))
+    g.set(yscale="log")
+    plt.xticks(rotation=90)
+    plt.show()
+
+def multi_contributors_barplot():
+    idx = 0
+    while all_loggedin_contributors.iloc[idx]["type"] == "Bot":
+        idx+=1
+    data = [{"number of repos contributed to": i+1, "number of accounts": 0} for i in range(len(all_loggedin_contributors.iloc[idx]["contributions"]))]
+    for index, row in all_loggedin_contributors.iterrows():
+        if (row["type"] == "Bot"): continue
+        nb_repos_contributed_to = len(row["contributions"])-1
+        data[nb_repos_contributed_to]["number of accounts"] += 1
+    data = pd.DataFrame(data)
+    g = sns.barplot(data, x="number of repos contributed to", y="number of accounts", color="orange")
+    plt.yscale("log")
+    plt.show()
+
+avg_contributors_per_category_barplot()
+contributions_years_scatterplot()
+multi_contributors_barplot()