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