diff --git a/README.md b/README.md
index d6e4033a6a498462d3ac174d13b8f4cd9987d1c7..c73b0201e81e417936be09a1cfc9ddfd66cc8739 100644
--- a/README.md
+++ b/README.md
@@ -13,9 +13,6 @@ In the Python version you will find :
 - Explainer - A tool to help explain the results from a MANOCCA test. You can for instance use it to check the power with regard to the number of PCs kept, of the main loadings of some PCs.
 - the rest is mostly functionalities under development. 
 
-# Get started
-For the python version, enter the Python repositories, follow the installation instructions below and 
-
 # Python Installation
 Start by creating a Python venv in the directory with the requirements.txt file. You can run the command :
 
@@ -43,7 +40,7 @@ Follow these steps :
 - Launch you docker engine (ex : launch the docker application)
 - Then run the following command in your terminal while in the the MANOCCA/python directory (or prompt in windows)
 - docker build -t manocca_docker .
-- docker run -it test1
+- docker run -it manocca_docker
 
 This will allow you to run an interactive terminal with the right environment to make MANOCCA work. If you want to use your personal data, you can add a repository in MANOCCA/python/your_data_directory and the data will be copied in the docker build command and you can access it within the interactive docker. If your dataset is too big, consider looking at the docker documentation to access data from an interactiver container.
 Remark : jupyter notebook might be tricky to run from a container, so use the Example_manocca_script.py to get started. 
diff --git a/python/requirements.txt b/python/requirements.txt
index 37abb64314277113aac94a182b582fc4f1532c47..d9b106e99ee512009378e418910d015c76f0e305 100644
--- a/python/requirements.txt
+++ b/python/requirements.txt
@@ -42,7 +42,6 @@ nbclient==0.6.7
 nbconvert==7.0.0
 nbformat==5.4.0
 nest-asyncio==1.5.5
-networkx==3.2.1
 notebook==6.4.12
 numpy==1.21.2
 packaging==21.3
diff --git a/python/src/explainer.py b/python/src/explainer.py
index 80021ab3eb9a11b0762210e4a35428a23155dbc5..829a24de501e26ccb3576dc01055d4f924691133 100644
--- a/python/src/explainer.py
+++ b/python/src/explainer.py
@@ -6,7 +6,7 @@ from manova import MANOVA
 from univariate import UNIVARIATE
 
 from tools.h_clustering import cluster_corr
-from tools.build_graph import get_tree, build_graph
+#from tools.build_graph import get_tree, build_graph
 
 import plotly.express as px
 from plotly.subplots import make_subplots