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{
"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)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.10"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}
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