如何以峰峦图展示降水数据
前言
本期使用joypy对降水数据处理，探索气象可视化的多元性。
降水数据是气象学中一个重要的指标，它对于了解和预测天气变化非常关键。在本期中，我们将使用 joypy 库来进行降水数据的可视化，展示降水的变化趋势和分布情况。
joypy 是一个基于 matplotlib 的 Python 库，用于创建美观的峰峦图（Ridge Plot）。峰峦图可以同时显示多个组别的分布情况，非常适合用于展示降水数据的多元性。
在接下来的代码中，我们将使用 joypy 来创建降水数据的峰峦图，并展示降水的季节变化和年际变化。让我们开始吧！ joypy地址：https://github.com/sbebo/joypy 镜像：气象分析3.9
In [42]:
!pip install joypy -i https://pypi.mirrors.ustc.edu.cn/simple/Looking in indexes: https://pypi.mirrors.ustc.edu.cn/simple/
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In [1]:
import joypy
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import cm
from sklearn.datasets import load_iris
np.random.seed(42)
df = pd.DataFrame(np.random.poisson(10,(24,7)))
df.columns = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
df.head()Monday | Tuesday | Wednesday | Thursday | Friday | Saturday | Sunday | |
|---|---|---|---|---|---|---|---|
0 | 12 | 6 | 11 | 14 | 7 | 8 | 9 |
1 | 11 | 8 | 10 | 7 | 11 | 11 | 8 |
2 | 12 | 6 | 7 | 8 | 10 | 5 | 3 |
3 | 9 | 13 | 8 | 6 | 13 | 12 | 13 |
4 | 9 | 14 | 8 | 8 | 12 | 15 | 13 |
In [2]:
%matplotlib inline
x_range = list(range(24))
fig, axes = joypy.joyplot(df, kind="values", x_range=x_range)
axes[-1].set_xticks(x_range);
生成随机降水月数据
In [3]:
time = pd.date_range(start='2000-01-01', end='2023-12-31', freq='d')
np.random.seed(42)
rain = np.random.uniform(0, 100, size=len(time))
pre = pd.DataFrame({'datetime':time, 'rain(mm)':rain})
print(pre) datetime rain(mm)
0 2000-01-01 37.454012
1 2000-01-02 95.071431
2 2000-01-03 73.199394
3 2000-01-04 59.865848
4 2000-01-05 15.601864
... ... ...
8761 2023-12-27 67.136801
8762 2023-12-28 52.315815
8763 2023-12-29 89.863893
8764 2023-12-30 16.439268
8765 2023-12-31 80.410925
[8766 rows x 2 columns]计算极端降水日数
先设置一个极端降水阈值。设为95%。
In [4]:
# 将日期列设置为索引：
pre['datetime'] = pd.to_datetime(pre['datetime'])
pre.set_index('datetime', inplace=True)
# 计算极端降水阈值：
threshold = pre['rain(mm)'].quantile(0.95)
# 按年份分组，然后计算每月的极端降水日数：
extreme_precipitation_days = pre[pre['rain(mm)'] > threshold].resample('M').size()
# 添加年份和极端降水日数到原始表格中：
pre['year'] = pre.index.year
pre['quarter'] = pre.index.quarter
pre['month'] = pre.index.month
pre['extreme_precipitation_days'] = extreme_precipitation_days这样你就可以得到一个包含每年极端降水日数的pandas Series对象extreme_precipitation_days。
In [5]:
prerain(mm) | year | quarter | month | extreme_precipitation_days | |
|---|---|---|---|---|---|
datetime | |||||
2000-01-01 | 37.454012 | 2000 | 1 | 1 | NaN |
2000-01-02 | 95.071431 | 2000 | 1 | 1 | NaN |
2000-01-03 | 73.199394 | 2000 | 1 | 1 | NaN |
2000-01-04 | 59.865848 | 2000 | 1 | 1 | NaN |
2000-01-05 | 15.601864 | 2000 | 1 | 1 | NaN |
... | ... | ... | ... | ... | ... |
2023-12-27 | 67.136801 | 2023 | 4 | 12 | NaN |
2023-12-28 | 52.315815 | 2023 | 4 | 12 | NaN |
2023-12-29 | 89.863893 | 2023 | 4 | 12 | NaN |
2023-12-30 | 16.439268 | 2023 | 4 | 12 | NaN |
2023-12-31 | 80.410925 | 2023 | 4 | 12 | 2.0 |
8766 rows × 5 columns
绘图部分
In [6]:
%matplotlib inline
labels=[y if y%1==0 else None for y in list(pre.year.unique())]
fig, axes = joypy.joyplot(pre, by="year", column="extreme_precipitation_days", labels=labels, range_style='own',
grid="y", linewidth=1, legend=False, fade=True, figsize=(20,12),
title="joypy preciption test",
kind="counts", bins=50)
显示效果欠佳，还是直接看降水量分布
In [7]:
# 创建山峦图
fig, ax = joypy.joyplot(pre,
by='year',
column='rain(mm)',
range_style='own',
grid='y',
linewidth=1,
fade=True,
legend=False,
kind="counts", bins=30,
figsize=(20,12),
title='Precipitation Over Years')
设置一下x轴范围，画一下年分布、季度分布、月分布
In [8]:
fig, ax = joypy.joyplot(pre,
by='year',
column='rain(mm)',
grid='y',
linewidth=1,
fade=True,
legend=False,
range_style='all',
x_range=[0,110],
kind="counts", bins=50,
figsize=(20,12),
title='Precipitation Over Years')
In [11]:
fig, ax = joypy.joyplot(pre,
by='quarter',
column='rain(mm)',
grid='y',
linewidth=0.8,
fade=True,
legend=False,
range_style='all',
x_range=[0,110],
kind="counts", bins=50,
figsize=(20,12),
title='Precipitation Over quarter ')/opt/conda/lib/python3.9/site-packages/joypy/joyplot.py:582: UserWarning: Glyph 9 ( ) missing from current font.
fig.tight_layout(h_pad=h_pad)
/opt/conda/lib/python3.9/site-packages/IPython/core/events.py:89: UserWarning: Glyph 9 ( ) missing from current font.
func(*args, **kwargs)
/opt/conda/lib/python3.9/site-packages/IPython/core/pylabtools.py:134: UserWarning: Glyph 9 ( ) missing from current font.
fig.canvas.print_figure(bytes_io, **kw)
In [10]:
fig, ax = joypy.joyplot(pre,
by='month',
column='rain(mm)',
grid='y',
linewidth=0.8,
fade=True,
legend=False,
range_style='all',
x_range=[0,110],
kind="counts", bins=50,
figsize=(20,12),
title='Precipitation Over months')
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原始发表：2024-01-18，如有侵权请联系 cloudcommunity@tencent.com 删除
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