update pandas

godaai · Nov 29, 2023 · 43bfae8 · 43bfae8
1 parent f0fe65d
commit 43bfae8
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Showing 7 changed files with 61 additions and 78 deletions.
diff --git a/ch-pandas/dataframe-merge-concat.ipynb b/ch-pandas/dataframe-merge-concat.ipynb
@@ -15,6 +15,7 @@
     "\n",
     "```{figure} ../img/ch-pandas/merge.svg\n",
     "---\n",
+    "width: 500px\n",
     "name: merge-img\n",
     "---\n",
     "对两个 DataFrame 进行 merge 操作\n",

diff --git a/ch-pandas/dataframe-pivot-melt.ipynb b/ch-pandas/dataframe-pivot-melt.ipynb
@@ -25,7 +25,7 @@
   },
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-   "execution_count": 14,
+   "execution_count": 34,
    "metadata": {
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@@ -67,7 +67,7 @@
   },
   {
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-   "execution_count": 15,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -333,7 +333,7 @@
        "16      Monitor         2    5000  presented  "
       ]
      },
-     "execution_count": 15,
+     "execution_count": 35,
      "metadata": {},
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@@ -369,7 +369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -484,7 +484,7 @@
        "Trantow-Barrows                15000.0  1.333333"
       ]
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-     "execution_count": 16,
+     "execution_count": 36,
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@@ -502,7 +502,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -579,7 +579,7 @@
        "              Wendy Yule     44250.000000  3.000000"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -597,7 +597,7 @@
   },
   {
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-   "execution_count": 18,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [
     {
@@ -736,7 +736,7 @@
        "              Wendy Yule            3.0     2.0      NaN  "
       ]
      },
-     "execution_count": 18,
+     "execution_count": 38,
      "metadata": {},
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@@ -765,7 +765,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -835,7 +835,7 @@
        "              Wendy Yule     44250.000000"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -857,17 +857,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/4n/v40br47s46ggrjm9bdm64lwh0000gn/T/ipykernel_34035/1265594602.py:1: FutureWarning: The provided callable <function mean at 0x7fedb7434dc0> is currently using DataFrameGroupBy.mean. In a future version of pandas, the provided callable will be used directly. To keep current behavior pass the string \"mean\" instead.\n",
-      "  pd.pivot_table(sales_df, index=[\"Manager\",\"Rep\"], values=[\"Price\"], aggfunc=[np.mean, len])\n"
-     ]
-    },
     {
      "data": {
       "text/html": [
@@ -953,13 +945,13 @@
        "              Wendy Yule     44250.000000     4"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pd.pivot_table(sales_df, index=[\"Manager\",\"Rep\"], values=[\"Price\"], aggfunc=[np.mean, len])"
+    "pd.pivot_table(sales_df, index=[\"Manager\",\"Rep\"], values=[\"Price\"], aggfunc=[\"mean\", len])"
    ]
   },
   {
@@ -973,7 +965,7 @@
   },
   {
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-   "execution_count": 21,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
@@ -1185,7 +1177,7 @@
        "All                                      1.764706  "
       ]
      },
-     "execution_count": 21,
+     "execution_count": 41,
      "metadata": {},
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     }
@@ -1207,7 +1199,7 @@
   },
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-   "execution_count": 22,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -1401,7 +1393,7 @@
        "              won                 1       0        0  "
       ]
      },
-     "execution_count": 22,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1429,7 +1421,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [
     {
@@ -1562,7 +1554,7 @@
        "             won                 0       0        0  "
       ]
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-     "execution_count": 23,
+     "execution_count": 43,
      "metadata": {},
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     }
@@ -1580,7 +1572,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
@@ -1714,7 +1706,7 @@
        "              won               1       0        0  "
       ]
      },
-     "execution_count": 24,
+     "execution_count": 44,
      "metadata": {},
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@@ -1734,7 +1726,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -1801,7 +1793,7 @@
        "2           3  John    88       79       90"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 45,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1820,7 +1812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
@@ -1931,7 +1923,7 @@
        "8           3  John  History     90"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }

diff --git a/docs/_sources/ch-pandas/dataframe-merge-concat.ipynb b/docs/_sources/ch-pandas/dataframe-merge-concat.ipynb
@@ -15,6 +15,7 @@
     "\n",
     "```{figure} ../img/ch-pandas/merge.svg\n",
     "---\n",
+    "width: 500px\n",
     "name: merge-img\n",
     "---\n",
     "对两个 DataFrame 进行 merge 操作\n",