{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"toc": true
},
"source": [
"Table of Contents
\n",
""
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#全部行都能输出\n",
"from IPython.core.interactiveshell import InteractiveShell\n",
"InteractiveShell.ast_node_interactivity = \"all\""
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 字符串函数"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"基本和python内置的字符串方法一样"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2个类似字符串元素的函数"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### np.char.add(a, b)字符串的拼接,类似相对于字符串的+运算\n",
"a b 是两个ndarray对象， 这两个对象的元素都必须全是字符串，其作用是把对应位置的字符串进行加法运算。 \n",
"要求是a b的形状相同， 或者满足广播规则！"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['123', '456', '789'], dtype='\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchar\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'1'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m# 找不到就报错\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32mD:\\Anaconda3\\lib\\site-packages\\numpy\\core\\defchararray.py\u001b[0m in \u001b[0;36mindex\u001b[1;34m(a, sub, start, end)\u001b[0m\n\u001b[0;32m 752\u001b[0m \"\"\"\n\u001b[0;32m 753\u001b[0m return _vec_string(\n\u001b[1;32m--> 754\u001b[1;33m a, integer, 'index', [sub, start] + _clean_args(end))\n\u001b[0m\u001b[0;32m 755\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 756\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mValueError\u001b[0m: substring not found"
]
}
],
"source": [
"np.char.index(a, '1') # 找不到就报错"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 三个分割的方法"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### np.char.split(a, 分割符， 分割次数)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['112,a1', '1asda1', '11asd', '1a232'], dtype='