如何在 Python 中將數據分為雨季和旱季？

Question

正在使用的數據圖片

我有一組時間序列數據，按月查看平均風速。 我正在嘗試編寫一些代碼，以便我可以：

1. 將月份分為干燥（5 月至 10 月）和潮濕（11 月至 4 月）季節。
2. 生成兩個不同的文件，分別包含每年的旱季和雨季。

我對python相當陌生，所以任何幫助都將不勝感激。

Answer 1

假設您將數據保存在 pandas Dataframe df中。

import pandas as pd

# parse the date to datetime:

date = pd.to_datetime(df['date'], format="%Y-%m")

# Get month numbers for the two seasons
wet_months = [11, 12, 1, 2, 3, 4]
dry_months = [month for month in range(1, 13) if month not in wet_months]

# Now partition the data into two tables
# Select each row that has a month in the given season using `.loc`.

df_wet = df.loc[date.dt.month.isin(wet_months)]
df_dry = df.loc[date.dt.month.isin(dry_months)]

# dataframe index seems to be arbitrary in your question
# so I'd probably drop indexes before saving to file. Or save the file without index.

df_wet = df_wet.reset_index(drop=True)
df_dry = df_dry.reset_index(drop=True)
# This way the tables get new range indexes starting from zero
# instead of remembering their index from the original `df`.

# now go ahead and save to .csv or any other output format
df_wet.to_csv("wet.csv")
df_dry.to_csv("dry.csv")