{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 定义要写入的数据\n",
    "data = [\n",
    "    ['王五', '19', '河北', 'kk']\n",
    "]\n",
    "\n",
    "# 创建DataFrame对象\n",
    "df = pd.DataFrame(data, columns=['name', 'age', 'city', 'mark'])\n",
    "\n",
    "# 将DataFrame写入CSV文件\n",
    "df.to_csv('../data/llm_test.csv', index=False, mode='a', header=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 读取CSV文件到DataFrame\n",
    "df = pd.read_csv('../data/llm_test.csv')\n",
    "# 修改特定行列的数据\n",
    "row_index = 0  # 要修改的行索引，除去表头，从0开始\n",
    "column_name = 'age'  # 要修改的列名\n",
    "new_value = '2345'  # 修改后的值\n",
    "\n",
    "df.loc[row_index, column_name] = new_value\n",
    "# 将修改后的DataFrame写回到CSV文件\n",
    "df.to_csv('../data/llm_test.csv', index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name    2\n",
      "age     2\n",
      "city    2\n",
      "mark    2\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 读取CSV文件到DataFrame\n",
    "df = pd.read_csv('../data/llm_test.csv')\n",
    "\n",
    "# 查找满足特定条件的行数据\n",
    "condition = df['age'] == 100  # 以Column1列为例，查找值为'Value1'的行\n",
    "filtered_data = df[condition]\n",
    "\n",
    "# 打印查找结果\n",
    "print(filtered_data)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  name  age city mark\n",
      "0   张三  100   河北   kk\n",
      "1   赵四   19   河北   kk\n",
      "2   赵五  100   河北   kk\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('../data/llm_test.csv').head(3)\n",
    "print(df)"
   ]
  }
 ],
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