|
78 | 78 | "import pandas as pd\n",
|
79 | 79 | "import numpy as np\n",
|
80 | 80 | "\n",
|
| 81 | + "rng = np.random.default_rng(2)\n", |
| 82 | + "\n", |
81 | 83 | "df = pd.DataFrame(\n",
|
82 | 84 | " {\"strings\": [\"Adam\", \"Mike\"], \"ints\": [1, 3], \"floats\": [1.123, 1000.23]}\n",
|
83 | 85 | ")\n",
|
|
100 | 102 | "outputs": [],
|
101 | 103 | "source": [
|
102 | 104 | "weather_df = pd.DataFrame(\n",
|
103 |
| - " np.random.rand(10, 2) * 5,\n", |
| 105 | + " rng.standard_normal(10, 2) * 5,\n", |
104 | 106 | " index=pd.date_range(start=\"2021-01-01\", periods=10),\n",
|
105 | 107 | " columns=[\"Tokyo\", \"Beijing\"],\n",
|
106 | 108 | ")\n",
|
|
157 | 159 | "metadata": {},
|
158 | 160 | "outputs": [],
|
159 | 161 | "source": [
|
160 |
| - "df = pd.DataFrame(np.random.randn(5, 5))\n", |
| 162 | + "df = pd.DataFrame(rng.standard_normal(5, 5))\n", |
161 | 163 | "df.style.hide(subset=[0, 2, 4], axis=0).hide(subset=[0, 2, 4], axis=1)"
|
162 | 164 | ]
|
163 | 165 | },
|
|
302 | 304 | " columns=df.columns,\n",
|
303 | 305 | " ),\n",
|
304 | 306 | " css_class=\"pd-tt\",\n",
|
305 |
| - " props=\"visibility: hidden; position: absolute; z-index: 1; border: 1px solid #000066;\"\n", |
306 |
| - " \"background-color: white; color: #000066; font-size: 0.8em;\"\n", |
307 |
| - " \"transform: translate(0px, -24px); padding: 0.6em; border-radius: 0.5em;\",\n", |
| 307 | + " props=\"visibility: hidden;\"\n", |
| 308 | + " \"position: absolute;\"\n", |
| 309 | + " \"z-index: 1;\"\n", |
| 310 | + " \"border: 1px solid #000066;\"\n", |
| 311 | + " \"background-color: white;\"\n", |
| 312 | + " \"color: #000066;\"\n", |
| 313 | + " \"font-size: 0.8em;\"\n", |
| 314 | + " \"transform: translate(0px, -24px);\"\n", |
| 315 | + " \"padding: 0.6em;\"\n", |
| 316 | + " \"border-radius: 0.5em;\",\n", |
308 | 317 | " )\n",
|
309 | 318 | ")"
|
310 | 319 | ]
|
|
602 | 611 | "metadata": {},
|
603 | 612 | "outputs": [],
|
604 | 613 | "source": [
|
605 |
| - "np.random.seed(0)\n", |
606 |
| - "df2 = pd.DataFrame(np.random.randn(10, 4), columns=[\"A\", \"B\", \"C\", \"D\"])\n", |
| 614 | + "df2 = pd.DataFrame(rng.standard_normal(10, 4), columns=[\"A\", \"B\", \"C\", \"D\"])\n", |
607 | 615 | "df2.style"
|
608 | 616 | ]
|
609 | 617 | },
|
|
812 | 820 | ")\n",
|
813 | 821 | "s.set_tooltips(\n",
|
814 | 822 | " tt,\n",
|
815 |
| - " props=\"visibility: hidden; position: absolute; z-index: 1; border: 1px solid #000066;\"\n", |
816 |
| - " \"background-color: white; color: #000066; font-size: 0.8em;\"\n", |
817 |
| - " \"transform: translate(0px, -24px); padding: 0.6em; border-radius: 0.5em;\",\n", |
| 823 | + " props=\"visibility: hidden;\"\n", |
| 824 | + " \"position: absolute; z-index:\"\n", |
| 825 | + " \"1; border: 1px solid #000066;\"\n", |
| 826 | + " \"background-color: white;\"\n", |
| 827 | + " \"color: #000066;\"\n", |
| 828 | + " \"font-size: 0.8em;\"\n", |
| 829 | + " \"transform: translate(0px, -24px);\"\n", |
| 830 | + " \"padding: 0.6em;\"\n", |
| 831 | + " \"border-radius: 0.5em;\",\n", |
818 | 832 | ")"
|
819 | 833 | ]
|
820 | 834 | },
|
|
894 | 908 | "outputs": [],
|
895 | 909 | "source": [
|
896 | 910 | "df3 = pd.DataFrame(\n",
|
897 |
| - " np.random.randn(4, 4),\n", |
| 911 | + " rng.standard_normal(4, 4),\n", |
898 | 912 | " pd.MultiIndex.from_product([[\"A\", \"B\"], [\"r1\", \"r2\"]]),\n",
|
899 | 913 | " columns=[\"c1\", \"c2\", \"c3\", \"c4\"],\n",
|
900 | 914 | ")\n",
|
|
1606 | 1620 | "\n",
|
1607 | 1621 | "\n",
|
1608 | 1622 | "@widgets.interact\n",
|
1609 |
| - "def f(h_neg=(0, 359, 1), h_pos=(0, 359), s=(0.0, 99.9), l=(0.0, 99.9)):\n", |
| 1623 | + "def f(h_neg=(0, 359, 1), h_pos=(0, 359), s=(0.0, 99.9), l_var=(0.0, 99.9)):\n", |
1610 | 1624 | " return df2.style.background_gradient(\n",
|
1611 | 1625 | " cmap=sns.palettes.diverging_palette(\n",
|
1612 |
| - " h_neg=h_neg, h_pos=h_pos, s=s, l=l, as_cmap=True\n", |
| 1626 | + " h_neg=h_neg, h_pos=h_pos, s=s, l=l_var, as_cmap=True\n", |
1613 | 1627 | " )\n",
|
1614 | 1628 | " )"
|
1615 | 1629 | ]
|
|
1629 | 1643 | "source": [
|
1630 | 1644 | "def magnify():\n",
|
1631 | 1645 | " return [\n",
|
1632 |
| - " dict(selector=\"th\", props=[(\"font-size\", \"4pt\")]),\n", |
1633 |
| - " dict(selector=\"td\", props=[(\"padding\", \"0em 0em\")]),\n", |
1634 |
| - " dict(selector=\"th:hover\", props=[(\"font-size\", \"12pt\")]),\n", |
1635 |
| - " dict(\n", |
1636 |
| - " selector=\"tr:hover td:hover\",\n", |
1637 |
| - " props=[(\"max-width\", \"200px\"), (\"font-size\", \"12pt\")],\n", |
1638 |
| - " ),\n", |
| 1646 | + " {\"selector\": \"th\", \"props\": [(\"font-size\", \"4pt\")]},\n", |
| 1647 | + " {\"selector\": \"td\", \"props\": [(\"padding\", \"0em 0em\")]},\n", |
| 1648 | + " {\"selector\": \"th:hover\", \"props\": [(\"font-size\", \"12pt\")]},\n", |
| 1649 | + " {\n", |
| 1650 | + " \"selector\": \"tr:hover td:hover\",\n", |
| 1651 | + " \"props\": [(\"max-width\", \"200px\"), (\"font-size\", \"12pt\")],\n", |
| 1652 | + " },\n", |
1639 | 1653 | " ]"
|
1640 | 1654 | ]
|
1641 | 1655 | },
|
|
1645 | 1659 | "metadata": {},
|
1646 | 1660 | "outputs": [],
|
1647 | 1661 | "source": [
|
1648 |
| - "np.random.seed(25)\n", |
1649 |
| - "cmap = cmap = sns.diverging_palette(5, 250, as_cmap=True)\n", |
1650 |
| - "bigdf = pd.DataFrame(np.random.randn(20, 25)).cumsum()\n", |
| 1662 | + "cmap = sns.diverging_palette(5, 250, as_cmap=True)\n", |
| 1663 | + "bigdf = pd.DataFrame(rng.standard_normal(20, 25)).cumsum()\n", |
1651 | 1664 | "\n",
|
1652 | 1665 | "bigdf.style.background_gradient(cmap, axis=1).set_properties(\n",
|
1653 | 1666 | " **{\"max-width\": \"80px\", \"font-size\": \"1pt\"}\n",
|
|
1671 | 1684 | "metadata": {},
|
1672 | 1685 | "outputs": [],
|
1673 | 1686 | "source": [
|
1674 |
| - "bigdf = pd.DataFrame(np.random.randn(16, 100))\n", |
| 1687 | + "bigdf = pd.DataFrame(rng.standard_normal(16, 100))\n", |
1675 | 1688 | "bigdf.style.set_sticky(axis=\"index\")"
|
1676 | 1689 | ]
|
1677 | 1690 | },
|
|
2023 | 2036 | "metadata": {},
|
2024 | 2037 | "outputs": [],
|
2025 | 2038 | "source": [
|
2026 |
| - "with open(\"templates/myhtml.tpl\") as f:\n", |
2027 |
| - " print(f.read())" |
| 2039 | + "with open(\"templates/myhtml.tpl\") as f_temp:\n", |
| 2040 | + " print(f_temp.read())" |
2028 | 2041 | ]
|
2029 | 2042 | },
|
2030 | 2043 | {
|
|
2130 | 2143 | },
|
2131 | 2144 | "outputs": [],
|
2132 | 2145 | "source": [
|
2133 |
| - "with open(\"templates/html_style_structure.html\") as f:\n", |
2134 |
| - " style_structure = f.read()" |
| 2146 | + "with open(\"templates/html_style_structure.html\") as f_style:\n", |
| 2147 | + " style_structure = f_style.read()" |
2135 | 2148 | ]
|
2136 | 2149 | },
|
2137 | 2150 | {
|
|
2158 | 2171 | },
|
2159 | 2172 | "outputs": [],
|
2160 | 2173 | "source": [
|
2161 |
| - "with open(\"templates/html_table_structure.html\") as f:\n", |
2162 |
| - " table_structure = f.read()" |
| 2174 | + "with open(\"templates/html_table_structure.html\") as f_table:\n", |
| 2175 | + " table_structure = f_table.read()" |
2163 | 2176 | ]
|
2164 | 2177 | },
|
2165 | 2178 | {
|
|
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