python 读取各科成绩文件(scores.csv),完成以下需求,1.输出各科前15条数据,2.使用describe 输出语文成绩的统计性描述,3.添加一列数据,列名为date,其值为"2023-06-05",输出前5条数据,4.将新添加的date 转换成datetime类型,输出第1条数据的月份
时间: 2024-03-05 16:54:52 浏览: 150
好的,我会根据您的要求进行回答。以下是我的回答:
1. 读取各科成绩文件并输出各科前15条数据的代码:
```python
import pandas as pd
# 读取各科成绩文件
df_math = pd.read_csv('scores.csv', usecols=['id', 'math'])
df_english = pd.read_csv('scores.csv', usecols=['id', 'english'])
df_chinese = pd.read_csv('scores.csv', usecols=['id', 'chinese'])
# 输出各科前15条数据
print('Math scores:')
print(df_math.head(15))
print('\nEnglish scores:')
print(df_english.head(15))
print('\nChinese scores:')
print(df_chinese.head(15))
```
2. 使用describe输出语文成绩的统计性描述的代码:
```python
import pandas as pd
# 读取语文成绩文件
df_chinese = pd.read_csv('scores.csv', usecols=['id', 'chinese'])
# 输出语文成绩的统计性描述
print(df_chinese['chinese'].describe())
```
3. 添加一列数据,并输出前5条数据的代码:
```python
import pandas as pd
# 读取各科成绩文件
df_math = pd.read_csv('scores.csv', usecols=['id', 'math'])
df_english = pd.read_csv('scores.csv', usecols=['id', 'english'])
df_chinese = pd.read_csv('scores.csv', usecols=['id', 'chinese'])
# 添加一列数据
df_math['date'] = '2023-06-05'
df_english['date'] = '2023-06-05'
df_chinese['date'] = '2023-06-05'
# 输出前5条数据
print('Math scores:')
print(df_math.head(5))
print('\nEnglish scores:')
print(df_english.head(5))
print('\nChinese scores:')
print(df_chinese.head(5))
```
4. 将新添加的date转换成datetime类型,并输出第1条数据的月份的代码:
```python
import pandas as pd
# 读取各科成绩文件
df_math = pd.read_csv('scores.csv', usecols=['id', 'math'])
df_english = pd.read_csv('scores.csv', usecols=['id', 'english'])
df_chinese = pd.read_csv('scores.csv', usecols=['id', 'chinese'])
# 添加一列数据并转换成datetime类型
df_math['date'] = pd.to_datetime('2023-06-05')
df_english['date'] = pd.to_datetime('2023-06-05')
df_chinese['date'] = pd.to_datetime('2023-06-05')
# 输出第1条数据的月份
print(df_math['date'][0].month)
```
希望我的回答能够帮助到您!
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