diff --git a/examples/data/1d/tracer[0]-avgxy(z)-1.plt b/examples/data/1d/tracer[0]-avgxy(z)-1.plt
new file mode 100644
index 0000000000000000000000000000000000000000..35fbdf224031b6ce69e101911ac88b98cf5e8fea
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-1.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 5.006209
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diff --git a/examples/data/1d/tracer[0]-avgxy(z)-2.plt b/examples/data/1d/tracer[0]-avgxy(z)-2.plt
new file mode 100644
index 0000000000000000000000000000000000000000..06ddf6e42832f88d907b392b91b1a7aa3dfdf383
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-2.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 10.000035
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diff --git a/examples/data/1d/tracer[0]-avgxy(z)-3.plt b/examples/data/1d/tracer[0]-avgxy(z)-3.plt
new file mode 100644
index 0000000000000000000000000000000000000000..8d3881154e7b7b7ca6c62f3b5532915658cc81b5
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-3.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 15.000340
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diff --git a/examples/data/1d/tracer[0]-avgxy(z)-4.plt b/examples/data/1d/tracer[0]-avgxy(z)-4.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ae0da61e8cfb6d3d2adf5182e75a4ffdd73017a2
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-4.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 20.000645
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diff --git a/examples/data/1d/tracer[0]-avgxy(z)-5.plt b/examples/data/1d/tracer[0]-avgxy(z)-5.plt
new file mode 100644
index 0000000000000000000000000000000000000000..91e4f67bbb0de3f95dad69b8fc1ada6409648d22
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-5.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 25.000950
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diff --git a/examples/data/1d/tracer[0]-avgxy(z)-6.plt b/examples/data/1d/tracer[0]-avgxy(z)-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..a36aa7bed115fe1aa581ff896da6f282dc6d227d
--- /dev/null
+++ b/examples/data/1d/tracer[0]-avgxy(z)-6.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-1.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-1.plt
new file mode 100644
index 0000000000000000000000000000000000000000..3516557fe0ae274442156d64c37279e4826d5ec8
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-1.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 5.006209
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-2.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-2.plt
new file mode 100644
index 0000000000000000000000000000000000000000..c6b5abd430cb3c111451784d5116ff4b14b467b7
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-2.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 10.000035
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-3.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-3.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ab758960ab439c7bc3cfc0ff237f52c8689c567f
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-3.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 15.000340
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-4.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-4.plt
new file mode 100644
index 0000000000000000000000000000000000000000..b73d8aef5c20fce5b4d01ec97eae7d08079a5ff5
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-4.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 20.000645
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-5.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-5.plt
new file mode 100644
index 0000000000000000000000000000000000000000..52662a9e15c00ef4bcf5c1783cbffea9ef214af4
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-5.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 25.000950
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diff --git a/examples/data/1d/tracer[0]-variance-avgxy(z)-6.plt b/examples/data/1d/tracer[0]-variance-avgxy(z)-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..c0797357597a21d4b6e3831e413a057509560667
--- /dev/null
+++ b/examples/data/1d/tracer[0]-variance-avgxy(z)-6.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-1.plt b/examples/data/1d/tracer[1]-avgxy(z)-1.plt
new file mode 100644
index 0000000000000000000000000000000000000000..72367e1f53d9ef8e2f82e7a1f87d2341a3405fa5
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-1.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 5.006209
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-2.plt b/examples/data/1d/tracer[1]-avgxy(z)-2.plt
new file mode 100644
index 0000000000000000000000000000000000000000..abcf8993e913e943b5682f7846442c3b27ea3ab5
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-2.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 10.000035
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-3.plt b/examples/data/1d/tracer[1]-avgxy(z)-3.plt
new file mode 100644
index 0000000000000000000000000000000000000000..159c9c12abf11f3b4ffad7e145cc8045d76a2b0a
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-3.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 15.000340
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-4.plt b/examples/data/1d/tracer[1]-avgxy(z)-4.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ef4b0ed931eb28f3c541c9f86b25be7770c98714
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-4.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 20.000645
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-5.plt b/examples/data/1d/tracer[1]-avgxy(z)-5.plt
new file mode 100644
index 0000000000000000000000000000000000000000..44372d3ab28bdd915e368fc58c5a9885f7b87793
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-5.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 25.000950
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diff --git a/examples/data/1d/tracer[1]-avgxy(z)-6.plt b/examples/data/1d/tracer[1]-avgxy(z)-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..2c1f744edd69eb50f86d4aa3d309acb9a3a16cb2
--- /dev/null
+++ b/examples/data/1d/tracer[1]-avgxy(z)-6.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "C(z)"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-1.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-1.plt
new file mode 100644
index 0000000000000000000000000000000000000000..7c6211792c1c18d9bd2cc3fd2a300e50c219668e
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-1.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 5.006209
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-2.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-2.plt
new file mode 100644
index 0000000000000000000000000000000000000000..c53ffbd925aa81578eb74eba322c5ef96df54bf9
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-2.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 10.000035
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-3.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-3.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ab465ba8863857f47998063e1e4ada93a84de212
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-3.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 15.000340
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-4.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-4.plt
new file mode 100644
index 0000000000000000000000000000000000000000..b277f71d6e5e7f1ab88e4fb9a46053f11e812fc0
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-4.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 20.000645
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-5.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-5.plt
new file mode 100644
index 0000000000000000000000000000000000000000..f6831f897f1535f1f20cb5371f1ef896f648afe0
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-5.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 25.000950
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diff --git a/examples/data/1d/tracer[1]-variance-avgxy(z)-6.plt b/examples/data/1d/tracer[1]-variance-avgxy(z)-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..157d63a31a536396457d06a320a7f39e9cb8ad31
--- /dev/null
+++ b/examples/data/1d/tracer[1]-variance-avgxy(z)-6.plt
@@ -0,0 +1,67 @@
+ TITLE = "nse-3D [F(Z)]"
+ VARIABLES = "Z", "(c'c')"
+ ZONE I = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/data/2d/Theta(x,y)-1.plt b/examples/data/2d/Theta(x,y)-1.plt
new file mode 100644
index 0000000000000000000000000000000000000000..f97e03683de96d2a6a058d458d5e0bae7ffbca14
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-1.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 5.006209
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diff --git a/examples/data/2d/Theta(x,y)-2.plt b/examples/data/2d/Theta(x,y)-2.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ef5d2af9406ffe129e7d388e3de16afc038270fa
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-2.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 10.000035
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diff --git a/examples/data/2d/Theta(x,y)-3.plt b/examples/data/2d/Theta(x,y)-3.plt
new file mode 100644
index 0000000000000000000000000000000000000000..93df27ef7ac69c50ebcdab608d13f6653525737d
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-3.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 15.000340
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diff --git a/examples/data/2d/Theta(x,y)-4.plt b/examples/data/2d/Theta(x,y)-4.plt
new file mode 100644
index 0000000000000000000000000000000000000000..ce6198d3dea2b096fc2476f16f0277c96d17aab9
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-4.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 20.000645
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diff --git a/examples/data/2d/Theta(x,y)-5.plt b/examples/data/2d/Theta(x,y)-5.plt
new file mode 100644
index 0000000000000000000000000000000000000000..9b2371e082f0cdd5b9af1c5b1b47b2e4b9c4207f
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-5.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 25.000950
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diff --git a/examples/data/2d/Theta(x,y)-6.plt b/examples/data/2d/Theta(x,y)-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..72890d3815b3be41799c79018b6a077e164fa06a
--- /dev/null
+++ b/examples/data/2d/Theta(x,y)-6.plt
@@ -0,0 +1,6147 @@
+ TITLE = "nse-3D [F_i(X,Y), i=1 .. 1]"
+ VARIABLES = "X", "Y", "z = 0.5"
+ ZONE I = 96, J = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/data/3d/tracer[0]-6.nsx b/examples/data/3d/tracer[0]-6.nsx
new file mode 100644
index 0000000000000000000000000000000000000000..566bf3d8b4e8de72ec91f7995605ec5d6bc3f1fd
Binary files /dev/null and b/examples/data/3d/tracer[0]-6.nsx differ
diff --git a/examples/data/3d/tracer[0]-6.plt b/examples/data/3d/tracer[0]-6.plt
new file mode 100644
index 0000000000000000000000000000000000000000..48908c13ba70afb0d89ee8952ca0a23a8d5752b9
--- /dev/null
+++ b/examples/data/3d/tracer[0]-6.plt
@@ -0,0 +1,393219 @@
+ TITLE = "nse-3D [F(X,Y,Z)]"
+ VARIABLES = "X", "Y", "Z", "C"
+ ZONE I = 96, J = 64, K = 64, DATAPACKING = POINT, SOLUTIONTIME = 30.001255
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diff --git a/examples/example.ipynb b/examples/example.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..4939d83ab1e05ab5f882a1e3fcb64bbac98d3df4
--- /dev/null
+++ b/examples/example.ipynb
@@ -0,0 +1,195 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import plotter as pt"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot 1d data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fname = 'data/1d/tracer[0]-avgxy(z)-6.plt'\n",
+    "pt.plot(fname)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot multiple 1d data on the same fig"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fname1 = 'data/1d/tracer[0]-avgxy(z)-6.plt'\n",
+    "fname2 = 'data/1d/tracer[1]-avgxy(z)-6.plt'\n",
+    "pt.multiple_plot([fname1, fname2])"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot animation of a 1d data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fname = 'data/1d/tracer\\[0\\]-avgxy(z)-*.plt'\n",
+    "pt.ani_plot(fname, oname='tracer0.gif')"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot 2d data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fname = 'data/2d/Theta(x,y)-6.plt'\n",
+    "pt.plot_contour(fname)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot animation of a 2d data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fname = 'data/2d/Theta\\(x,y\\)-*.plt'\n",
+    "pt.ani_plot_contour(fname, oname='Theta.gif')"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot an averaged by x and y coordinates 3D data: *.plt or *.nsx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fname = 'data/3d/tracer[0]-6.plt'\n",
+    "pt.avg_plot(fname)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/plotter/Plotter.py b/plotter/Plotter.py
index c6876eff820fb53c32c5455b1dc01c506b7fbe2e..6e8467a69a6292243ea510ef1cfe9a64e3361063 100755
--- a/plotter/Plotter.py
+++ b/plotter/Plotter.py
@@ -142,9 +142,10 @@ class Plotter:
 
             for read_data in self.file_data:
                 plt.plot(read_data.data[x_name], read_data.data[y_name], linewidth=4)
-                plt.legend(self.filename)
-                plt.xlabel(x_name, fontsize=10, fontweight='bold')
-                plt.ylabel(y_name, fontsize=10, fontweight='bold')
+
+            plt.legend(self.filename)
+            plt.xlabel(x_name, fontsize=10, fontweight='bold')
+            plt.ylabel(y_name, fontsize=10, fontweight='bold')
             
             if self.if_manual_plot: plt.show()
             else: plt.close(fig)
diff --git a/plotter/ProcData.py b/plotter/ProcData.py
index 542cf7226c995f115c547b8565ae7843d4c6dfe9..141774afcaa3d1a24335adef03c43a4abdef64c3 100755
--- a/plotter/ProcData.py
+++ b/plotter/ProcData.py
@@ -25,8 +25,10 @@ class ProcData:
         with open(self.filename, "r") as file:
             file_data = file.read().split('\n')
         file.close()
+        
+        idx =  character_indexes(file_data[1], '=')
 
-        names = [GetVariableName(variable_name) for variable_name in file_data[1].split('=')[1].split(',')]
+        names = [GetVariableName(variable_name) for variable_name in file_data[1][idx[0] : ].split(',')]
         self.variable_names = np.array(names, dtype=object)
     
     def __get_variable_names_bin(self):