2024-05-07 02:09:35 发布
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如何在数据框中填充nan值? 我的数据是这样的
id state zone xxx AP south xxx AP xxx AP xxx AP xxx delhi north xxx delhi xxx delhi xxx delhi xxx delhi
如何根据state列(我们已经知道AP只属于south)来填充zone列中缺少的值,如何使用熊猫填充值
state
AP
south
zone
(id,state)
df = pd.DataFrame(data={"id":["x","x","x","x"], "state":["AP","Delhi","AP","Delhi"], "zone":["sount","north",np.nan,np.nan]}) res = df.sort_values(['id','state','zone']) res = df.groupby(['id','state'],as_index=False)['zone'].ffill() print(res)
id state zone 0 x AP sount 1 x Delhi north 2 x AP sount 3 x Delhi north
df['zone'] = df.groupby(['state'],as_index=False)['zone'].transform(lambda x:x.ffill()) print(df)
我认为你需要:
df = df.sort_values(by="state").ffill() print(df)
(id,state)
填充zone
我认为你需要:
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