[英]Python: Change values in a pandas DataFrame column based on multiple conditions in Python
[英]Multiple if conditions in pandas dataframe - Python
我正在關注這個問題的答案
我有一個這樣的df
:
score_1 score_2
1.11 NaN
2.22 3.33
NaN 3.33
NaN NaN
........
計算final_score
的規則是,我們要求至少有一個分數是non-null
,如果 NULL 中的一個分數,那么 final_score 將等於另一個分數(它具有所有權重)這是要復制的代碼:
import numpy as np
import pandas as pd
df = pd.DataFrame({
'score_1': [1.11, 2.22, np.nan],
'score_2': [np.nan, 3.33, 3.33]
})
def final_score(df):
if (df['score_1'] != np.nan) and (df['score_2'] != np.nan):
print('I am condition one')
return df['score_1'] * 0.2 + df['score_2'] * 0.8
elif (df['score_1'] == np.nan) and (df['score_2'] != np.nan):
print('I am the condition two')
return df['score_2']
elif (df['score_1'] != np.nan) and (df['score_2'] == np.nan):
print('I am the condition three')
return df['score_1']
elif (df['score_1'] == np.nan) and (df['score_2'] == np.nan):
print('I am the condition four')
return np.nan
df['final_score'] = df.apply(final_score, axis=1)
print(df)
這給了我 output:
score_1 score_2 final_score
1.11 NaN NaN
2.22 3.33 3.108
NaN 3.33 NaN
NaN NaN NaN
........
但我預期的 output 如下:
score_1 score_2 final_score
1.11 NaN 1.11
2.22 3.33 3.108
NaN 3.33 3.33
NaN NaN NaN
........
第一行和第三行不是我期望的結果,有人可以幫助我,我的代碼有什么問題嗎? 非常感謝。
讓我們使用 np.where 應用您的條件
df['final_score'] =np.where(df.notna().all(1),df['score_1'] * 0.2 + df['score_2'] * 0.8,df.mean(1))
score_1 score_2 final_score
0 1.11 NaN 1.110
1 2.22 3.33 3.108
2 NaN 3.33 3.330
3 NaN NaN NaN
使用 np.isnan() 進行比較應該可以解決問題
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