move file locations

Selecting Subsets of Data in Pandas part 1.ipynb → Learn-Pandas/Selecting Subsets/Selecting Subsets of Data in Pandas part 1.ipynb

@@ -38,7 +38,7 @@
     "# The anatomy of a DataFrame and a Series\n",
     "The pandas library has two primary containers of data, the DataFrame and the Series. You will spend nearly all your time working with both of the objects when you use pandas. The DataFrame is used more than the Series, so let's take a look at an image of it first. \n",
     "\n",
-    "![](images/01_dataframe_anatomy.png)\n",
+    "![](../images/01_dataframe_anatomy.png)\n",
     "\n",
     "This images comes with some added illustrations to highlight its components. At first glance, the DataFrame looks like any other two-dimensional table of data that you have seen. It has rows and it has columns. Technically, there are three main components of the DataFrame.\n",
     "\n",
@@ -68,33 +68,33 @@
     "### Example selecting some columns and all rows\n",
     "Let's see some images of subset selection. We will first look at a sample DataFrame with fake data.\n",
     "\n",
-    "![](images/01_sample_df.png)\n",
+    "![](../images/01_sample_df.png)\n",
     "\n",
     "Let's say we want to select just the columns `color`, `age`, and `height` but keep all the rows. \n",
     "\n",
-    "![](images/01_just_cols.png)\n",
+    "![](../images/01_just_cols.png)\n",
     "\n",
     "Our final DataFrame would look like this:\n",
     "\n",
-    "![](images/01_just_cols2.png)\n",
+    "![](../images/01_just_cols2.png)\n",
     "\n",
     "### Example selecting some rows and all columns\n",
     "We can also make selections that select just some of the rows. Let's select the rows with labels `Aaron` and `Dean` along with all of the columns:\n",
     "\n",
-    "![](images/01_just_rows.png)\n",
+    "![](../images/01_just_rows.png)\n",
     "\n",
     "Our final DataFrame would like:\n",
     "\n",
-    "![](images/01_just_rows2.png)\n",
+    "![](../images/01_just_rows2.png)\n",
     "\n",
     "### Example selecting some rows and some columns\n",
     "Let's combine the selections from above and select the columns `color`, `age`, and `height` for only the rows with labels `Aaron` and `Dean`.\n",
     "\n",
-    "![](images/01_rows_cols.png)\n",
+    "![](../images/01_rows_cols.png)\n",
     "\n",
     "Our final DataFrame would look like this:\n",
     "\n",
-    "![](images/01_rows_cols2.png)\n",
+    "![](../images/01_rows_cols2.png)\n",
     "\n",
     "\n",
     "# Pandas dual references: by label and by integer location\n",
@@ -264,7 +264,7 @@
     }
    ],
    "source": [
-    "df = pd.read_csv('data/sample_data.csv', index_col=0)\n",
+    "df = pd.read_csv('../../data/sample_data.csv', index_col=0)\n",
     "df"
    ]
   },
@@ -3875,7 +3875,7 @@
     }
    ],
    "source": [
-    "df2 = pd.read_csv('data/sample_data2.csv')\n",
+    "df2 = pd.read_csv('../../data/sample_data2.csv')\n",
     "df2"
    ]
   },
@@ -4826,7 +4826,7 @@
     }
    ],
    "source": [
-    "df = pd.read_csv('data/food_inspections.csv')\n",
+    "df = pd.read_csv('../../data/food_inspections.csv')\n",
     "df.head()"
    ]
   },
@@ -4947,7 +4947,9 @@
   {
    "cell_type": "code",
    "execution_count": 88,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"
@@ -4964,7 +4966,9 @@
   {
    "cell_type": "code",
    "execution_count": 89,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"
@@ -4981,7 +4985,9 @@
   {
    "cell_type": "code",
    "execution_count": 90,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"
@@ -4998,7 +5004,9 @@
   {
    "cell_type": "code",
    "execution_count": 91,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"
@@ -5015,7 +5023,9 @@
   {
    "cell_type": "code",
    "execution_count": 92,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"
@@ -5032,7 +5042,9 @@
   {
    "cell_type": "code",
    "execution_count": 93,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# your code here"