Merge pull request statsmodels#4853 from bashtage/remove-recarray-data

REF: Remove recarrays from datasets and related code

Author: josef-pkt

docs/source/anova.rst

@@ -17,7 +17,7 @@ Examples
     import statsmodels.api as sm
     from statsmodels.formula.api import ols
 
-    moore = sm.datasets.get_rdataset("Moore", "car",
+    moore = sm.datasets.get_rdataset("Moore", "carData",
                                      cache=True) # load data
     data = moore.data
     data = data.rename(columns={"partner.status":

docs/source/contingency_tables.rst

@@ -267,7 +267,7 @@ methods and attributes.
     data = sm.datasets.china_smoking.load()
 
     mat = np.asarray(data.data)
-    tables = [np.reshape(x.tolist()[1:], (2, 2)) for x in mat]
+    tables = [np.reshape(x.tolist(), (2, 2)) for x in mat]
 
     st = sm.stats.StratifiedTable(tables)
     print(st.summary())

docs/source/datasets/index.rst

@@ -30,7 +30,7 @@ The `Rdatasets project <http://vincentarelbundock.github.io/Rdatasets/>`__ gives
 .. ipython:: python
 
    import statsmodels.api as sm
-   duncan_prestige = sm.datasets.get_rdataset("Duncan", "car")
+   duncan_prestige = sm.datasets.get_rdataset("Duncan", "carData")
    print(duncan_prestige.__doc__)
    duncan_prestige.data.head(5)
 

examples/notebooks/markov_autoregression.ipynb

@@ -19,9 +19,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
@@ -70,9 +68,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Get the RGNP data to replicate Hamilton\n",
@@ -91,9 +87,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "res_hamilton.summary()"
@@ -111,9 +105,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, axes = plt.subplots(2, figsize=(7,7))\n",
@@ -142,9 +134,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "print(res_hamilton.expected_durations)"
@@ -180,9 +170,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Get the dataset\n",
@@ -203,9 +191,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "res_kns.summary()"
@@ -221,9 +207,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, axes = plt.subplots(3, figsize=(10,7))\n",
@@ -274,9 +258,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Get the dataset\n",
@@ -314,9 +296,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "mod_filardo = sm.tsa.MarkovAutoregression(\n",
@@ -330,9 +310,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "res_filardo.summary()"
@@ -348,9 +326,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "fig, ax = plt.subplots(figsize=(12,3))\n",
@@ -371,9 +347,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "res_filardo.expected_durations[0].plot(\n",
@@ -390,23 +364,23 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python2"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.6"
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }