diff --git a/volia/plot.py b/volia/plot.py
new file mode 100644
index 0000000..9aa3645
--- /dev/null
+++ b/volia/plot.py
@@ -0,0 +1,71 @@
+import argparse
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+
+from core.data import read_features, read_lst, read_labels
+from utils import SubCommandRunner
+
+
+def scatter_plot(features: str, labels: str, outfile: str):
+    """Generate a simple scatter plot. Mainly used for 
+    data visualisation processed with tsne or algorithm like
+    this later.
+
+    Args:
+        features (str): Features file in 2d or 3d
+        labels (str): Labels file
+        outfile (str) : output file
+    """
+
+    id_to_features = read_features(args.features)
+    ids = [ key for key in id_to_features.keys() ]
+    utt2label = read_labels(labels)
+    
+    features = [ id_to_features[id_] for id_ in ids ]
+    features = np.vstack(features)
+
+    labels_list = [ utt2label[id_][0] for id_ in ids ]
+
+    features_T = features.transpose()
+    print("Number of labels: ", len(np.unique(labels_list)))
+    df = pd.DataFrame(dict(
+        x=features_T[0],
+        y=features_T[1],
+        label=labels_list))
+
+    groups = df.groupby('label')
+
+    # Plot
+    fig, ax = plt.subplots()
+
+    for label, group in groups:
+        p = ax.plot(group.x, group.y, marker='o', linestyle='', ms=1, label=label)
+    ax.legend()
+    plt.savefig(outfile)
+    print("Your plot is saved well (no check of this affirmation)")
+    
+
+
+if __name__ == '__main__':
+
+    # Main parser
+    parser = argparse.ArgumentParser(description="")
+    subparsers = parser.add_subparsers(title="action")
+
+    # with label
+    parser_scatter = subparsers.add_parser("scatter")
+    parser_scatter.add_argument("features", type=str, help="define the main features file")
+    parser_scatter.add_argument("--labels", default=None, type=str, help="specify the labels of each utterance/element")
+    parser_scatter.add_argument("--outfile", default="./out.pdf", type=str, help="Specify the output file (better in pdf)")
+    parser_scatter.set_defaults(which="scatter")
+
+    # Parse
+    args = parser.parse_args()
+
+    # Run commands
+    runner = SubCommandRunner({
+        "scatter" : scatter_plot
+    })
+    
+    runner.run(args.which, args.__dict__, remove="which")
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