Change pandas attribute syntax to selector syntax for column names

Author: Hugo Bowne-Anderson

notebooks/1.Probability_a_simulated_introduction.ipynb

@@ -227,7 +227,7 @@
    "outputs": [],
    "source": [
     "# Store lengths in a pandas series\n",
-    "lengths = df_12.blength"
+    "lengths = df_12['blength']"
    ]
   },
   {
@@ -615,7 +615,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_fortis = df_12.loc[df_12.species == 'fortis']\n",
+    "df_fortis = df_12.loc[df_12['species'] == 'fortis']\n",
     "sum(df_fortis.blength > 10)/len(df_fortis)"
    ]
   },
@@ -625,7 +625,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df_scandens = df_12.loc[df_12.species == 'scandens']\n",
+    "df_scandens = df_12.loc[df_12['species'] == 'scandens']\n",
     "sum(df_scandens.blength > 10)/len(df_scandens)"
    ]
   },

notebooks/2.Parameter_estimation_hypothesis_testing.ipynb

@@ -324,8 +324,8 @@
    "source": [
     "# Import and view head of data\n",
     "df_12 = pd.read_csv('../data/finch_beaks_2012.csv')\n",
-    "df_fortis = df_12.loc[df_12.species == 'fortis']\n",
-    "df_scandens = df_12.loc[df_12.species == 'scandens']"
+    "df_fortis = df_12.loc[df_12['species'] == 'fortis']\n",
+    "df_scandens = df_12.loc[df_12['species'] == 'scandens']"
    ]
   },
   {
@@ -341,7 +341,7 @@
     "    μ_1 = pm.Normal('μ_1', mu=10, sd=5)\n",
     "    σ_1 = pm.Lognormal('σ_1', 0, 10)\n",
     "    # Gaussian Likelihood\n",
-    "    y_1 = pm.Normal('y_1', mu=μ_1, sd=σ_1, observed=df_fortis.blength)"
+    "    y_1 = pm.Normal('y_1', mu=μ_1, sd=σ_1, observed=df_fortis['blength'])"
    ]
   },
   {
@@ -446,8 +446,8 @@
     "    μ_2 = pm.Normal('μ_2', mu=10, sd=5)\n",
     "    σ_2 = pm.Lognormal('σ_2', 0, 10)\n",
     "    # Gaussian Likelihoods\n",
-    "    y_1 = pm.Normal('y_1', mu=μ_1, sd=σ_1, observed=df_fortis.blength)\n",
-    "    y_2 = pm.Normal('y_2', mu=μ_2, sd=σ_2, observed=df_scandens.blength)\n",
+    "    y_1 = pm.Normal('y_1', mu=μ_1, sd=σ_1, observed=df_fortis['blength'])\n",
+    "    y_2 = pm.Normal('y_2', mu=μ_2, sd=σ_2, observed=df_scandens['blength'])\n",
     "    # Calculate the effect size and its uncertainty.\n",
     "    diff_means = pm.Deterministic('diff_means', μ_1 - μ_2)\n",
     "    pooled_sd = pm.Deterministic('pooled_sd', \n",