{"id":811,"date":"2023-12-10T05:14:29","date_gmt":"2023-06-24T23:33:12","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/index.php\/2023\/11\/30\/python%e3%81%aepandas%e3%83%a2%e3%82%b8%e3%83%a5%e3%83%bc%e3%83%ab%e3%81%ae%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%ab\/"},"modified":"2025-08-01T02:40:15","modified_gmt":"2025-07-31T17:40:15","slug":"python%e3%81%aepandas%e3%83%a2%e3%82%b8%e3%83%a5%e3%83%bc%e3%83%ab%e3%81%ae%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%ab","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/python%e3%81%aepandas%e3%83%a2%e3%82%b8%e3%83%a5%e3%83%bc%e3%83%ab%e3%81%ae%e3%83%81%e3%83%a5%e3%83%bc%e3%83%88%e3%83%aa%e3%82%a2%e3%83%ab\/","title":{"rendered":"Python\u306ePandas\u30e2\u30b8\u30e5\u30fc\u30eb\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb"},"content":{"rendered":"<h2>Python\u306ePandas\u30e2\u30b8\u30e5\u30fc\u30eb<\/h2>\n<ul class=\"post-ul\">\n<li>Pandas is an open source library in Python. It provides ready to use high-performance data structures and data analysis tools.<\/li>\n<li>Pandas module runs on top of NumPy and it is popularly used for data science and data analytics.<\/li>\n<li>NumPy is a low-level data structure that supports multi-dimensional arrays and a wide range of mathematical array operations. Pandas has a higher-level interface. It also provides streamlined alignment of tabular data and powerful time series functionality.<\/li>\n<li>DataFrame is the key data structure in Pandas. It allows us to store and manipulate tabular data as a 2-D data structure.<\/li>\n<li>Pandas provides a rich feature-set on the DataFrame. For example, data alignment, data statistics, slicing, grouping, merging, concatenating data, etc.<\/li>\n<\/ul>\n<hr \/>\n<h2>Pandas\u306e\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3068\u59cb\u3081\u65b9<\/h2>\n<p>Pandas\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u305f\u3081\u306b\u306f\u3001Python 2.7\u4ee5\u4e0a\u304c\u5fc5\u8981\u3067\u3059\u3002conda\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001\u4ee5\u4e0b\u306e\u30b3\u30de\u30f3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>conda install pandas\r\n<\/code><\/pre>\n<p>\u3082\u3057PIP\u3092\u4f7f\u7528\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001\u4e0b\u8a18\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u3066pandas\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<pre class=\"post-pre\"><code>pip3.7 install pandas\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/8-0.png\" alt=\"Python Install Pandas Module\" \/><\/div>\n<p>Python\u30b9\u30af\u30ea\u30d7\u30c8\u306bPandas\u3068NumPy\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u3092\u8ffd\u52a0\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n<pre class=\"post-pre\"><code>import pandas as pd\r\nimport numpy as np\r\n<\/code><\/pre>\n<p>\u30d1\u30f3\u30c0\u306fNumPy\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u4f9d\u5b58\u3057\u3066\u3044\u308b\u305f\u3081\u3001\u3053\u306e\u4f9d\u5b58\u95a2\u4fc2\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<hr \/>\n<h2>Pandas\u30e2\u30b8\u30e5\u30fc\u30eb\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u69cb\u9020<\/h2>\n<p>Pandas\u30e2\u30b8\u30e5\u30fc\u30eb\u306f3\u3064\u306e\u30c7\u30fc\u30bf\u69cb\u9020\u3092\u63d0\u4f9b\u3057\u3066\u304a\u308a\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/p>\n<ul class=\"post-ul\">\n<li>Series: It is a 1-D size-immutable array like structure having homogeneous data.<\/li>\n<li>DataFrames: It is a 2-D size-mutable tabular structure with heterogeneously typed columns.<\/li>\n<li>Panel: It is a 3-D, size-mutable array.<\/li>\n<\/ul>\n<hr \/>\n<h2>\u30d1\u30f3\u30c0\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0<\/h2>\n<p>DataFrame\u306f\u6700\u3082\u91cd\u8981\u3067\u5e83\u304f\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u30c7\u30fc\u30bf\u69cb\u9020\u3067\u3042\u308a\u3001\u30c7\u30fc\u30bf\u3092\u683c\u7d0d\u3059\u308b\u305f\u3081\u306e\u6a19\u6e96\u7684\u306a\u65b9\u6cd5\u3067\u3059\u3002DataFrame\u306f\u3001SQL\u30c6\u30fc\u30d6\u30eb\u3084\u30b9\u30d7\u30ec\u30c3\u30c9\u30b7\u30fc\u30c8\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u3088\u3046\u306b\u3001\u30c7\u30fc\u30bf\u304c\u884c\u3068\u5217\u306b\u6574\u5217\u3057\u3066\u3044\u307e\u3059\u3002DataFrame\u306b\u306f\u3001\u30cf\u30fc\u30c9\u30b3\u30fc\u30c9\u3067\u30c7\u30fc\u30bf\u3092\u5165\u529b\u3059\u308b\u304b\u3001CSV\u30d5\u30a1\u30a4\u30eb\u3001tsv\u30d5\u30a1\u30a4\u30eb\u3001Excel\u30d5\u30a1\u30a4\u30eb\u3001SQL\u30c6\u30fc\u30d6\u30eb\u306a\u3069\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30b3\u30f3\u30b9\u30c8\u30e9\u30af\u30bf\u3092\u4f7f\u7528\u3057\u3066\u3001DataFrame\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>pandas.DataFrame(data, index, columns, dtype, copy)\r\n<\/code><\/pre>\n<p>\u4ee5\u4e0b\u306b\u306f\u30d1\u30e9\u30e1\u30fc\u30bf\u306e\u7c21\u5358\u306a\u8aac\u660e\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<ul class=\"post-ul\">\n<li>data &#8211; create a DataFrame object from the input data. It can be list, dict, series, Numpy ndarrays or even, any other DataFrame.<\/li>\n<li>index &#8211; has the row labels<\/li>\n<li>columns &#8211; used to create column labels<\/li>\n<li>dtype &#8211; used to specify the data type of each column, optional parameter<\/li>\n<li>copy &#8211; used for copying data, if any<\/li>\n<\/ul>\n<p>DataFrame\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5\u306f\u305f\u304f\u3055\u3093\u3042\u308a\u307e\u3059\u3002\u8f9e\u66f8\u3084\u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u307e\u305f\u3001\u30bf\u30d7\u30eb\u306e\u30ea\u30b9\u30c8\u3084CSV\u3001Excel\u30d5\u30a1\u30a4\u30eb\u306a\u3069\u304b\u3089\u3082\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3067\u306f\u3001\u8f9e\u66f8\u306e\u30ea\u30b9\u30c8\u304b\u3089DataFrame\u3092\u4f5c\u6210\u3059\u308b\u305f\u3081\u306e\u7c21\u5358\u306a\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>import pandas as pd\r\nimport numpy as np\r\ndf = pd.DataFrame({\r\n    \"State\": ['Andhra Pradesh', 'Maharashtra', 'Karnataka', 'Kerala', 'Tamil Nadu'],\r\n    \"Capital\": ['Hyderabad', 'Mumbai', 'Bengaluru', 'Trivandrum', 'Chennai'],\r\n    \"Literacy %\": [89, 77, 82, 97,85],\r\n    \"Avg High Temp(c)\": [33, 30, 29, 31, 32 ]\r\n})\r\nprint(df)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/24-0.png\" alt=\"Python pandas Dataframe\" \/><\/div>\n<hr \/>\n<h2>CSV\u304b\u3089\u30c7\u30fc\u30bf\u3092DataFrame\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u3002<\/h2>\n<p>\u79c1\u305f\u3061\u306fCSV\u30d5\u30a1\u30a4\u30eb\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u3066DataFrame\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002CSV\u30d5\u30a1\u30a4\u30eb\u306f\u30011\u884c\u3054\u3068\u306b1\u3064\u306e\u30c7\u30fc\u30bf\u30ec\u30b3\u30fc\u30c9\u304c\u3042\u308b\u30c6\u30ad\u30b9\u30c8\u30d5\u30a1\u30a4\u30eb\u3067\u3059\u3002\u30ec\u30b3\u30fc\u30c9\u5185\u306e\u5024\u306f\u300c\u30ab\u30f3\u30de\u300d\u6587\u5b57\u3067\u533a\u5207\u3089\u308c\u3066\u3044\u307e\u3059\u3002Pandas\u306f\u3001CSV\u30d5\u30a1\u30a4\u30eb\u306e\u5185\u5bb9\u3092DataFrame\u306b\u8aad\u307f\u8fbc\u3080\u305f\u3081\u306e\u4fbf\u5229\u306a\u30e1\u30bd\u30c3\u30c9\u3067\u3042\u308bread_csv()\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u30a4\u30f3\u30c9\u306e\u90fd\u5e02\u306e\u8a73\u7d30\u304c\u8a18\u8f09\u3055\u308c\u305f\u300ccities.csv\u300d\u3068\u3044\u3046\u30d5\u30a1\u30a4\u30eb\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306eCSV\u30d5\u30a1\u30a4\u30eb\u306f\u3001Python\u30b9\u30af\u30ea\u30d7\u30c8\u304c\u542b\u307e\u308c\u308b\u540c\u3058\u30c7\u30a3\u30ec\u30af\u30c8\u30ea\u306b\u4fdd\u5b58\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3053\u306e\u30d5\u30a1\u30a4\u30eb\u306f\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u30a4\u30f3\u30dd\u30fc\u30c8\u3067\u304d\u307e\u3059\uff1a<\/p>\n<pre class=\"post-pre\"><code>import pandas as pd\r\ndata =  pd.read_csv('cities.csv')\r\nprint(data)\r\n<\/code><\/pre>\n<p>\u79c1\u305f\u3061\u306e\u76ee\u7684\u306f\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u307f\u3001\u5206\u6790\u3057\u3066\u7d50\u8ad6\u3092\u51fa\u3059\u3053\u3068\u3067\u3059\u3002\u3057\u305f\u304c\u3063\u3066\u3001\u30c7\u30fc\u30bf\u3092\u8aad\u307f\u8fbc\u3080\u305f\u3081\u306b\u4fbf\u5229\u306a\u3069\u3093\u306a\u65b9\u6cd5\u3067\u3082\u4f7f\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001DataFrame\u306e\u30c7\u30fc\u30bf\u3092\u56fa\u5b9a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n<hr \/>\n<h2>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u306e\u30c7\u30fc\u30bf\u3092\u8abf\u67fb\u3059\u308b\u3002<\/h2>\n<p>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u540d\u524d\u3067\u5b9f\u884c\u3059\u308b\u3068\u3001\u30c6\u30fc\u30d6\u30eb\u5168\u4f53\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u3067\u89e3\u6790\u3059\u308b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u306f\u6570\u5343\u884c\u3042\u308a\u307e\u3059\u3002\u30c7\u30fc\u30bf\u3092\u89e3\u6790\u3059\u308b\u305f\u3081\u306b\u306f\u3001\u5927\u91cf\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u304b\u3089\u30c7\u30fc\u30bf\u3092\u78ba\u8a8d\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u30d1\u30f3\u30c0\u306f\u3001\u5fc5\u8981\u306a\u30c7\u30fc\u30bf\u306e\u307f\u3092\u78ba\u8a8d\u3059\u308b\u305f\u3081\u306e\u591a\u304f\u306e\u4fbf\u5229\u306a\u6a5f\u80fd\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002df.head(n)\u3092\u4f7f\u7528\u3057\u3066\u6700\u521d\u306en\u884c\u3092\u53d6\u5f97\u3057\u305f\u308a\u3001df.tail(n)\u3092\u4f7f\u7528\u3057\u3066\u6700\u5f8c\u306en\u884c\u3092\u8868\u793a\u3057\u305f\u308a\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304b\u3089\u6700\u521d\u306e2\u884c\u3068\u6700\u5f8c\u306e1\u884c\u3092\u8868\u793a\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>print(df.head(2))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/34-0.png\" alt=\"Head\" \/><\/div>\n<pre class=\"post-pre\"><code>print(df.tail(1))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/36-4.png\" alt=\"Values\" \/><\/div>\n<hr \/>\n<h3>1. \u30ec\u30b3\u30fc\u30c9\u306e\u7d71\u8a08\u7684\u306a\u6982\u8981\u306e\u53d6\u5f97<\/h3>\n<p>Note: This translation is a direct paraphrase of the original sentence in Japanese.<\/p>\n<p>df.describe()\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u306e\u7d71\u8a08\u7684\u306a\u30b5\u30de\u30ea\u30fc\uff08\u30ab\u30a6\u30f3\u30c8\u3001\u5e73\u5747\u3001\u6a19\u6e96\u504f\u5dee\u3001\u6700\u5c0f\u5024\u3001\u6700\u5927\u5024\u306a\u3069\uff09\u3092\u53d6\u5f97\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3067\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u300cLiteracy %\u300d\u5217\u306e\u7d71\u8a08\u7684\u306a\u30b5\u30de\u30ea\u30fc\u3092\u8868\u793a\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002\u3053\u308c\u3092\u884c\u3046\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u3092\u8ffd\u52a0\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>print(df['Literacy %'].describe())\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/41-0.png\" alt=\"Describe\" \/><\/div>\n<hr \/>\n<h3>2. \u30ec\u30b3\u30fc\u30c9\u306e\u30bd\u30fc\u30c8<\/h3>\n<p>df.sort_values(by=&#8221;Literacy %&#8221;, ascending=False)\u95a2\u6570\u3092\u4f7f\u3063\u3066\u3001\u4efb\u610f\u306e\u5217\u3067\u30ec\u30b3\u30fc\u30c9\u3092\u4e26\u3073\u66ff\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u300cLiteracy %\u300d\u5217\u3092\u964d\u9806\u3067\u4e26\u3073\u66ff\u3048\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>print(df.sort_values('Literacy %', ascending=False))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/46-0.png\" alt=\"Sort\" \/><\/div>\n<hr \/>\n<h3>3. \u30ec\u30b3\u30fc\u30c9\u3092\u30b9\u30e9\u30a4\u30b9\u3059\u308b\u3002<\/h3>\n<p>\u7279\u5b9a\u306e\u5217\u306e\u30c7\u30fc\u30bf\u3092\u3001\u5217\u540d\u3092\u4f7f\u7528\u3057\u3066\u62bd\u51fa\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\u3002\u4f8b\u3048\u3070\u3001\u300eCapital\u300f\u5217\u3092\u62bd\u51fa\u3059\u308b\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>df['Capital']\r\n<\/code><\/pre>\n<p>\u307e\u305f\u306f<\/p>\n<pre class=\"post-pre\"><code>(df.Capital)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/53-0.png\" alt=\"Slice Capitals\" \/><\/div>\n<pre class=\"post-pre\"><code>print(df[['State', 'Capital']])\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/55-0.png\" alt=\"Slicemultiplecol\" \/><\/div>\n<pre class=\"post-pre\"><code>df[0:3]\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/57-0.png\" alt=\"Slicerows\" \/><\/div>\n<hr \/>\n<h3>4. \u30c7\u30fc\u30bf\u306e\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0<\/h3>\n<p>\u5217\u5024\u306b\u30d5\u30a3\u30eb\u30bf\u30fc\u3092\u304b\u3051\u308b\u3053\u3068\u3082\u53ef\u80fd\u3067\u3059\u3002\u4f8b\u3048\u3070\u3001\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u306fLiteracy%\u304c90%\u3092\u8d85\u3048\u308b\u5217\u3092\u30d5\u30a3\u30eb\u30bf\u30ea\u30f3\u30b0\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>print(df[df['Literacy %']&gt;90])\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/62-0.png\" alt=\"Filter Lit\" \/><\/div>\n<pre class=\"post-pre\"><code>print(df[df['State'].isin(['Karnataka', 'Tamil Nadu'])])\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/64-0.png\" alt=\"Filter\" \/><\/div>\n<hr \/>\n<h3>5.\u3000\u5217\u306e\u540d\u524d\u3092\u5909\u66f4\u3059\u308b<\/h3>\n<p>\u5217\u306e\u540d\u524d\u3092\u6539\u540d\u3059\u308b<\/p>\n<p>df.rename()\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u5217\u306e\u540d\u524d\u3092\u5909\u66f4\u3059\u308b\u3053\u3068\u304c\u53ef\u80fd\u3067\u3059\u3002\u3053\u306e\u95a2\u6570\u306f\u3001\u53e4\u3044\u5217\u540d\u3068\u65b0\u3057\u3044\u5217\u540d\u3092\u5f15\u6570\u3068\u3057\u3066\u53d7\u3051\u53d6\u308a\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001&#8217;Literacy %&#8217;\u3068\u3044\u3046\u5217\u540d\u3092&#8217;Literacy percentage&#8217;\u306b\u5909\u66f4\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>df.rename(columns = {'Literacy %':'Literacy percentage'}, inplace=True)\r\nprint(df.head())\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/69-0.png\" alt=\"Rename\" \/><\/div>\n<hr \/>\n<h3>6. \u30c7\u30fc\u30bf\u306e\u6574\u7406<\/h3>\n<p>\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306f\u3001\u30c7\u30fc\u30bf\u3092\u51e6\u7406\u3057\u3066\u30c7\u30fc\u30bf\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3068\u30b9\u30e0\u30fc\u30ba\u306b\u52d5\u4f5c\u3059\u308b\u3088\u3046\u306b\u3059\u308b\u3053\u3068\u3092\u542b\u307f\u307e\u3059\u3002\u30c7\u30fc\u30bf\u6574\u7406\uff08\u30c7\u30fc\u30bf\u30e9\u30f3\u30b0\u30ea\u30f3\u30b0\uff09\u306f\u3001\u30de\u30fc\u30b8\u3001\u30b0\u30eb\u30fc\u30d7\u5316\u3001\u9023\u7d50\u306a\u3069\u306e\u30c7\u30fc\u30bf\u306e\u51e6\u7406\u624b\u6cd5\u3067\u3059\u3002Pandas\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u306f\u3001merge\uff08\uff09\u3001groupby\uff08\uff09\u304a\u3088\u3073concat\uff08\uff09\u306a\u3069\u306e\u4fbf\u5229\u306a\u95a2\u6570\u304c\u7528\u610f\u3055\u308c\u3066\u304a\u308a\u3001\u30c7\u30fc\u30bf\u30e9\u30f3\u30b0\u30ea\u30f3\u30b0\u306e\u30bf\u30b9\u30af\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u307e\u3059\u30022\u3064\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u4f5c\u6210\u3057\u3001\u30c7\u30fc\u30bf\u30e9\u30f3\u30b0\u30ea\u30f3\u30b0\u306e\u95a2\u6570\u3092\u793a\u3057\u3066\u3001\u3088\u308a\u826f\u304f\u7406\u89e3\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>import pandas as pd\r\n\r\nd = {  \r\n    'Employee_id': ['1', '2', '3', '4', '5'],\r\n    'Employee_name': ['Akshar', 'Jones', 'Kate', 'Mike', 'Tina']\r\n}\r\ndf1 = pd.DataFrame(d, columns=['Employee_id', 'Employee_name'])  \r\nprint(df1)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/74-0.png\" alt=\"Wrangling 1\" \/><\/div>\n<pre class=\"post-pre\"><code>import pandas as pd\r\n\r\ndata = {  \r\n    'Employee_id': ['4', '5', '6', '7', '8'],\r\n    'Employee_name': ['Meera', 'Tia', 'Varsha', 'Williams', 'Ziva']\r\n}\r\ndf2 = pd.DataFrame(data, columns=['Employee_id', 'Employee_name'])  \r\nprint(df2)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/76-0.png\" alt=\"Wrangling 2\" \/><\/div>\n<hr \/>\n<h4>a. \u7d71\u5408\u3059\u308b<\/h4>\n<p>\u3055\u3066\u3001\u4f5c\u6210\u3057\u305f2\u3064\u306e\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u3001&#8217;Employee_id&#8217;\u306e\u5024\u3092\u5229\u7528\u3057\u3066merge()\u95a2\u6570\u3067\u7d50\u5408\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>print(pd.merge(df1, df2, on='Employee_id'))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/81-0.png\" alt=\"Merging\" \/><\/div>\n<hr \/>\n<h4>\u30b0\u30eb\u30fc\u30d7\u5316<\/h4>\n<p>\u30b0\u30eb\u30fc\u30d7\u5316\u306f\u3001\u30c7\u30fc\u30bf\u3092\u7570\u306a\u308b\u30ab\u30c6\u30b4\u30ea\u306b\u53ce\u96c6\u3059\u308b\u30d7\u30ed\u30bb\u30b9\u3067\u3059\u3002\u4f8b\u3048\u3070\u3001\u4ee5\u4e0b\u306e\u4f8b\u3067\u306f\u3001\u300cEmployee_Name\u300d\u30d5\u30a3\u30fc\u30eb\u30c9\u306b\u300cMeera\u300d\u3068\u3044\u3046\u540d\u524d\u304c2\u56de\u8868\u793a\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3067\u3059\u306e\u3067\u3001\u300cEmployee_name\u300d\u5217\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>import pandas as pd\r\nimport numpy as np\r\n\r\ndata = {\r\n    'Employee_id': ['4', '5', '6', '7', '8'],\r\n    'Employee_name': ['Meera', 'Meera', 'Varsha', 'Williams', 'Ziva']\r\n}\r\ndf2 = pd.DataFrame(data)\r\n\r\ngroup = df2.groupby('Employee_name')\r\nprint(group.get_group('Meera'))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/86-0.png\" alt=\"Grouping\" \/><\/div>\n<hr \/>\n<h4>c. \u7d50\u5408\u3059\u308b (Ketsug\u014d suru)<\/h4>\n<p>\u30c7\u30fc\u30bf\u306e\u9023\u7d50\u306f\u3001\u4e00\u3064\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u5225\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u8ffd\u52a0\u3059\u308b\u3053\u3068\u3092\u610f\u5473\u3057\u307e\u3059\u3002Pandas\u306f\u3001DataFrame\u3092\u9023\u7d50\u3059\u308b\u305f\u3081\u306econcat()\u3068\u3044\u3046\u95a2\u6570\u3092\u63d0\u4f9b\u3057\u3066\u3044\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001DataFrame df1\u3068df2\u3092\u9023\u7d50\u3059\u308b\u5834\u5408\u3001\u6b21\u306e\u3088\u3046\u306b\u3057\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>print(pd.concat([df1, df2]))\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/91-0.png\" alt=\"Concatenation\" \/><\/div>\n<hr \/>\n<h2>\u8f9e\u66f8\u306e\u30b7\u30ea\u30fc\u30ba\u3092\u6e21\u3059\u3053\u3068\u3067\u3001\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u3092\u4f5c\u6210\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/h2>\n<p>\u30b7\u30ea\u30fc\u30ba\u3092\u4f5c\u6210\u3059\u308b\u306b\u306f\u3001pd.Series()\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u914d\u5217\u3092\u6e21\u3059\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u3001\u7c21\u5358\u306a\u30b7\u30ea\u30fc\u30ba\u3092\u4f5c\u6210\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<pre class=\"post-pre\"><code>series_sample = pd.Series([100, 200, 300, 400])\r\nprint(series_sample)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/96-0.png\" alt=\"Series Sample\" \/><\/div>\n<pre class=\"post-pre\"><code>d = {'Matches played' : pd.Series([400, 300, 200], index=['Sachin', 'Kohli', 'Raina']),\r\n'Position' : pd.Series([1, 2, 3, 4], index=['Sachin', 'Kohli', 'Raina', 'Dravid'])}\r\ndf = pd.DataFrame(d)\r\nprint(df)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/98-0.png\" alt=\"Df Dictseries\" \/><\/div>\n<hr \/>\n<h3>\u30ab\u30e9\u30e0\u306e\u9078\u629e\u3001\u8ffd\u52a0\u3001\u524a\u9664<\/h3>\n<p>\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304b\u3089\u7279\u5b9a\u306e\u5217\u3092\u9078\u629e\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u6700\u521d\u306e\u5217\u306e\u307f\u3092\u8868\u793a\u3059\u308b\u306b\u306f\u3001\u4e0a\u8a18\u306e\u30b3\u30fc\u30c9\u3092\u4ee5\u4e0b\u306e\u3088\u3046\u306b\u66f8\u304d\u63db\u3048\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<pre class=\"post-pre\"><code>d = {'Matches played' : pd.Series([400, 300, 200], index=['Sachin', 'Kohli', 'Raina']),\r\n 'Position' : pd.Series([1, 2, 3, 4], index=['Sachin', 'Kohli', 'Raina', 'Dravid'])}\r\ndf = pd.DataFrame(d)\r\nprint(df['Matches played'])\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/103-0.png\" alt=\"Col Selection\" \/><\/div>\n<pre class=\"post-pre\"><code>d = {'Matches played' : pd.Series([400, 300, 200], index=['Sachin', 'Kohli', 'Raina']),\r\n 'Position' : pd.Series([1, 2, 3, 4], index=['Sachin', 'Kohli', 'Raina', 'Dravid'])}\r\ndf = pd.DataFrame(d)\r\ndf['Runrate']=pd.Series([80, 70, 60, 50], index=['Sachin', 'Kohli', 'Raina', 'Dravid'])\r\nprint(df)\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/105-0.png\" alt=\"Col Addition\" \/><\/div>\n<pre class=\"post-pre\"><code>del df['Matches played']\r\n<\/code><\/pre>\n<p>\u307e\u305f\u306f<\/p>\n<pre class=\"post-pre\"><code>df.pop('Matches played')\r\n<\/code><\/pre>\n<div><img decoding=\"async\" class=\"post-images\" title=\"\" src=\"https:\/\/cdn.silicloud.com\/blog-img\/blog\/img\/65649bb1daa94e2bdf7c1901\/109-0.png\" alt=\"Delcolum\" \/><\/div>\n<hr \/>\n<h2>\u7d50\u8ad6<\/h2>\n<p>\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python\u306ePandas\u30e9\u30a4\u30d6\u30e9\u30ea\u306b\u3064\u3044\u3066\u7c21\u5358\u306a\u7d39\u4ecb\u3092\u3057\u307e\u3057\u305f\u3002\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u5206\u91ce\u3067\u4f7f\u7528\u3055\u308c\u308bPandas\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u30d1\u30ef\u30fc\u3092\u5f15\u304d\u51fa\u3059\u305f\u3081\u306e\u5b9f\u8df5\u7684\u306a\u4f8b\u3082\u884c\u3044\u307e\u3057\u305f\u3002\u307e\u305f\u3001Python\u30e9\u30a4\u30d6\u30e9\u30ea\u306e\u7570\u306a\u308b\u30c7\u30fc\u30bf\u69cb\u9020\u306b\u3082\u89e6\u308c\u307e\u3057\u305f\u3002\u53c2\u8003\u6587\u732e\uff1aPandas\u516c\u5f0f\u30a6\u30a7\u30d6\u30b5\u30a4\u30c8<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Python\u306ePandas\u30e2\u30b8\u30e5\u30fc\u30eb Pandas is an open source library in Python. 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