python:对excel表中温度列里连续三天大于35℃的气温用红色标记,并记为一次高温过程。统计高温过程的数量,并计算每次高温过程中每天的气温与35摄氏度之差的和,输出到新excel表中
时间: 2024-03-27 21:39:09 浏览: 104
好的,我可以帮你完成这个任务。首先,我们需要使用Python中的pandas库来读取和处理Excel表格。请确保你已经安装了pandas库。
以下是代码实现的步骤:
1. 导入需要的库
```python
import pandas as pd
import numpy as np
```
2. 读取Excel表格数据
```python
df = pd.read_excel('your_file_name.xlsx')
```
3. 判断温度是否大于35℃
```python
df['is_hot'] = np.where(df['temperature'] > 35, 1, 0)
```
4. 判断连续三天是否大于35℃
```python
df['is_hot_3d'] = df['is_hot'].rolling(window=3, min_periods=3).sum()
```
5. 标记高温过程
```python
df['hot_process'] = np.where(df['is_hot_3d'] == 3, 1, 0)
```
6. 统计高温过程数量
```python
hot_process_count = df['hot_process'].sum()
```
7. 计算每次高温过程中每天的气温与35摄氏度之差的和
```python
df['temp_diff'] = np.where(df['temperature'] > 35, df['temperature'] - 35, 0)
hot_process_sum = df.groupby('hot_process')['temp_diff'].sum()
```
8. 输出到新Excel表格中
```python
hot_process_sum.to_excel('your_output_file_name.xlsx')
```
完整的代码实现如下:
```python
import pandas as pd
import numpy as np
# 读取Excel表格数据
df = pd.read_excel('your_file_name.xlsx')
# 判断温度是否大于35℃
df['is_hot'] = np.where(df['temperature'] > 35, 1, 0)
# 判断连续三天是否大于35℃
df['is_hot_3d'] = df['is_hot'].rolling(window=3, min_periods=3).sum()
# 标记高温过程
df['hot_process'] = np.where(df['is_hot_3d'] == 3, 1, 0)
# 统计高温过程数量
hot_process_count = df['hot_process'].sum()
# 计算每次高温过程中每天的气温与35摄氏度之差的和
df['temp_diff'] = np.where(df['temperature'] > 35, df['temperature'] - 35, 0)
hot_process_sum = df.groupby('hot_process')['temp_diff'].sum()
# 输出到新Excel表格中
hot_process_sum.to_excel('your_output_file_name.xlsx')
```
注意替换代码中的文件名和路径。
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