fixed csv project

docs/source/user/index.rst

@@ -175,14 +175,8 @@ Setup
 
 Let's start by setting up the project as usual, though in this short case we would not need all the extensions::
 
-    from instrument import Instrument
-    from model import Model
-    from parameter import Parameter
-    from dataset import Dataset
-    from pipeline import Pipeline
-    from run import Run
-
-    import numpy as np
+    import pandas as pd
+    from pykkn.dataset import Dataset
 
 In this case, it is important to add the panda framework as well because we will use this to store the CSV file::
 
@@ -192,20 +186,26 @@ In this case, it is important to add the panda framework as well because we will
 Inserting and storing of the data
 *********************************
 
-At first, we will store the CSV file as a variable which we can then add to dataset object. To do this, we use the function read_csv() from the panda framework::
+At first, we will store the CSV file as a variable which we can then add to dataset object. To do this, we use the function read_csv() from the panda framework.
+In the parameters of the function you put the name of the csv file. In this case the table is stored in the same folder as the example project. 
+That is why no further import path is needed. The second paramter in this case is called "sep=;". Is specifies how the data in the csv table are seperated::
 
-    df = pd.read_csv("test_data.csv")
+    df = pd.read_csv("exampleTable.csv", sep=';')
 
 Afterwards, we create a dataset object and add the df variable to this object::
 
-    dataset1 = Dataset("test_data.csv")
+    dataset1 = Dataset("from_csv_table")
     dataset1.data = df.values
 
+Before storing the hdf5 file set the storage path. In this case only a name is given::
+
+    dataset1.set_storage_path("from_csv_table.h5")
+
 To create the HDF5 file from this, we use the store() function::
 
     dataset1.store()
 
-The output of this short project can be seen below:
+The output of this short project can be seen below. By double-clicking on the "from_csv_table" object on the left you can open the window shwon in the left with stored data:
 
 .. image:: user-images/example-project-importCSV/csv_file_hdf5.jpg