<jupyter_start><jupyter_text>The Wind Resource> Characteristics of wind. Variations in season and day, turbulence etc. To have this connected to the real world please download the ANH data set from [Orsted lidar data](https://orsted.com/en/our-business/offshore-wind/wind-data) it is free and used in the examples below.[For kids](https://www.youtube.com/watch?v=QPlIrQQF9Rw)[Global wind atlas](https://globalwindatlas.info/)<jupyter_code>print("hest")
%matplotlib inline
import pandas as pd
import numpy as np
anh_df = pd.read_csv("data/wind_resource/LiDAR_Data_ANH_2013-2014.csv")
anh_df["1_WindSpeed"].hist(bins=np.arange(0,25.5,0.5), alpha=0.5, density=True)
anh_df["7_WindSpeed"].hist(bins=np.arange(0,25.5,0.5), alpha= 0.5, density=True)
anh_df["10_WindSpeed"].hist(bins=np.arange(0,25.5,0.5), alpha= 0.5, density=True)
for wspeed in anh_df.keys():
    if wspeed.endswith("WindSpeed"):
        print(wspeed, anh_df[wspeed].mean())
        anh_df[wspeed].hist(bins=np.arange(0,25.5,0.5), alpha= 0.5, density=True)
altitude_keys = [k for k in anh_df.keys() if "Altitude" in k]
print(anh_df[altitude_keys])
for k in anh_df.keys():
    print(k)
print(anh_df[["3_WindDirection","3_WindSpeed"]])<jupyter_output>3_WindDirection  3_WindSpeed
0                 205.9        17.28
1                 204.4        17.24
2                 205.0        17.30
3                 207.0        17.10
4                 208.9        16.71
...                 ...          ...
104579            289.1         9.39
104580            284.1         8.24
104581            287.6         8.46
104582            286.4         8.58
104583            288.5         8.90

[104584 rows x 2 columns]
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