numpy數組中數據的過濾

Question

我有一個 CSV 文件，其中包含來自世界不同地區的漲潮幅度的數據，我編寫了一個代碼來過濾從該 CSV 文件讀取的數據，代碼如下所示：

import pandas as pd
import numpy as np

df1=pd.read_csv("Tide Prediction.csv")
df1.columns = df1.iloc[0]        #To replace the header with the first row 
df1 = df1[1:]

df2=df1.rename(columns={df1.columns[3]: "location"}) 
dict = {'UTC': 'time',
    'degrees_east': 'longitude',
    'degress_west': 'latitude'}
df2['degrees_north'] = df2['degrees_north'].astype(float, errors = 'raise')
df2['degrees_east'] = df2['degrees_east'].astype(float, errors = 'raise')

c=np.where(degrees_north>8.06694 & degrees_north < 37.10028, [True]*6885393, [False]*6885393)

但這給了我一個錯誤

Answer 1

您可以between使用：

假設如下 dataframe

df = pd.DataFrame({'degrees_north': [8, 9, 37, 38]})
print(df)

# Output:
   degrees_north
0              8
1              9
2             37
3             38

>>> df['degrees_north'].between(8.06694, 37.10028, inclusive='neither')
0    False
1     True
2     True
3    False
Name: degrees_north, dtype: bool

Answer 2

這里np.where不是必須的，因為同樣的 output 如果只比較，只需要 add ()條件：

c=(degrees_north>8.06694) & (degrees_north < 37.10028)

c=np.where((degrees_north>8.06694) & (degrees_north < 37.10028), True, False)