diff --git a/src/analysis/overall_reduced_for_poster.py b/src/analysis/overall_reduced_for_poster.py
index b604c74..8a52197 100644
--- a/src/analysis/overall_reduced_for_poster.py
+++ b/src/analysis/overall_reduced_for_poster.py
@@ -67,6 +67,7 @@ def plot_license_type(contents, ax):
     contents.license_type.value_counts().sort_index().plot(
         kind='barh',
         ax=ax,
+        color="#0077bb",
         #ylabel="license type",
         #xlabel="repository count"
     )
@@ -84,6 +85,7 @@ def plot_contributing_file_present(contents, ax):
     pd.notna(contents.contributing_added).value_counts().plot(
         kind='barh',
         ax=ax,
+        color="#0077bb",
         #ylabel="contributing file",
         #xlabel="repository count"
     )
@@ -116,7 +118,7 @@ def plot_team_size(metadata, contributions, ax):
     counts, bins = np.histogram(max_team_size, bins)
     binlabels = [f"[{bins[i]} - {bins[i+1]})" for i in range(len(bins)-2)]
     binlabels += [f"[{bins[-2]} - {bins[-1]}]"]
-    ax.barh(binlabels, counts)
+    ax.barh(binlabels, counts, color="#0077bb")
     ax.bar_label(ax.containers[0])
     #ax.set(ylabel="maximum team size", xlabel="repository count")
     ax.set(xlabel="repository count")
@@ -132,7 +134,7 @@ def plot_readme_size(contents, ax, type="bar"):
     """
     bins = [0, 1, 300, 1500, 10000]
     binmeanings = ["none", "ultra-short", "short", "informative", "detailed"]
-    colours = ["#3875b1", "#f1882e", "#4d9d39", "#c73f30", "#8e6aba"]
+    colours = ["#0077bb", "#33bbee", "#009988", "#ee7733", "#cc3311"]
     if contents.readme_size.max() > bins[-1]:
         bins.append(contents.readme_size.max())
     counts, bins = np.histogram(contents.readme_size, bins)
diff --git a/src/analysis/repository_timeline_anon_for_poster.py b/src/analysis/repository_timeline_anon_for_poster.py
index a0ff6a2..f171104 100644
--- a/src/analysis/repository_timeline_anon_for_poster.py
+++ b/src/analysis/repository_timeline_anon_for_poster.py
@@ -77,8 +77,8 @@ def engagement_user_highlights(users, metadata, forks, stars, ax):
     user_forks["week_since_repo_creation"] = (user_forks.date - user_forks.created_at).dt.days // 7
     user_stars = pd.merge(stars[stars.user.isin(users)], metadata, on="github_user_cleaned_url")
     user_stars["week_since_repo_creation"] = (user_stars.date - user_stars.created_at).dt.days // 7
-    ax.scatter(user_forks.week_since_repo_creation, user_forks.user, marker="v", s=100, label="forked")
-    ax.scatter(user_stars.week_since_repo_creation, user_stars.user, marker="v", s=100, label="starred")
+    ax.scatter(user_forks.week_since_repo_creation, user_forks.user, marker="v", s=100, label="forked", c="#ee7733")
+    ax.scatter(user_stars.week_since_repo_creation, user_stars.user, marker="v", s=100, label="starred", c="#009988")
 
 def user_type_wrt_issues(issues, metadata, forks, stars, analysis_end_date, ax):
     """Plot every user's issue interaction type (opening issues, closing issues, both) with engagement highlight dates scattered on top.
@@ -120,7 +120,7 @@ def user_type_wrt_issues(issues, metadata, forks, stars, analysis_end_date, ax):
         y="user",
         hue="status",
         hue_order=["inactive", "opening", "closing", "both"],
-        palette=['#d62728', '#1f77b4', '#ff7f0e', '#2ca02c'],
+        palette=['#cc3311', '#0077bb', '#ee7733', '#009988'],
         marker="|",
         s=500,
         )
@@ -154,7 +154,7 @@ def contributor_team(contributions, metadata, forks, stars, axs):
         y="author",
         hue="active contributors",
         hue_order=["inactive", "active"],
-        palette=['#d62728', '#2ca02c'],
+        palette=['#cc3311', '#009988'],
         marker="|",
         s=500,
     )
@@ -167,6 +167,7 @@ def contributor_team(contributions, metadata, forks, stars, axs):
     team_size.plot(
         ax=axs[1],
         lw=2,
+        color="#0077bb",
         # xlabel="week since repo creation",
         ylabel="number of\ncontributors",
     )
@@ -177,6 +178,7 @@ def contributor_team(contributions, metadata, forks, stars, axs):
     contrib_pool.plot(
         ax=axs[1],
         lw=2,
+        color="#ee7733",
     )
 
 def no_open_and_closed_issues(issues, metadata, analysis_end_date, ax):
@@ -210,6 +212,7 @@ def no_open_and_closed_issues(issues, metadata, analysis_end_date, ax):
         ax=ax,
         x="week_since_repo_creation",
         y=["open issues", "closed issues"],
+        color=["#0077bb", "#ee7733"],
         lw=2,
         # xlabel="week since repo creation",
         ylabel="issue count"
@@ -242,7 +245,8 @@ def engagement(forks, stars, metadata, analysis_end_date, ax):
     engagement_df.plot(
         ax=ax,
         lw=2,
-        ylabel="count"
+        ylabel="count",
+        color=["#0077bb", "#ee7733"],
     )
     
 def calc_y_timeline(data):
@@ -304,8 +308,7 @@ def date_highlights(readme_history, contents, metadata, paper_data, ax, overlay_
     data = [ownership_added, usage_added, citation_added, citation_file_added, contributing_file_added, paper_published]
     ys = calc_y_timeline(data)
     labels = ["ownership heading (add/change)", "usage heading (add/change)", "citation in README (add/change)", "citation file added", "contributing file added", "mention in publication"]
-    prop_cycle = plt.rcParams['axes.prop_cycle']
-    colors = prop_cycle.by_key()['color']
+    colors = ["#0077bb", "#33bbee", "#009988", "#ee7733", "#cc3311", "#ee3377"]
     ymax = 100
     for i in range(len(data)):
         ax.scatter(data[i], ys[i], marker="^", s=100, label=labels[i], color=colors[i])