Pandas:根据其他列值有条件地替换值 [英] Pandas: Conditionally replace values based on other columns values

问题描述

我有一个如下所示的数据框 (df):

I have a dataframe (df) that looks like this:

                    environment     event   
time                    
2017-04-28 13:08:22     NaN         add_rd  
2017-04-28 08:58:40     NaN         add_rd  
2017-05-03 07:59:35     test        add_env
2017-05-03 08:05:14     prod        add_env
...

现在我的目标是对于 event 列中的每个 add_rd，在 environment 中关联的 NaN-value> 列应替换为字符串 RD.

Now my goal is for each add_rd in the event column, the associated NaN-value in the environment column should be replaced with a string RD.

                    environment     event   
time                    
2017-04-28 13:08:22     RD          add_rd  
2017-04-28 08:58:40     RD          add_rd  
2017-05-03 07:59:35     test        add_env
2017-05-03 08:05:14     prod        add_env
...

<小时>

到目前为止我做了什么

我偶然发现了 df['environment'] = df['environment].fillna('RD') 替换了 every NaN(这不是我要找的)，检测缺失值的 pd.isnull(df['environment']) 和 np.where(df['environment'], x,y) 这似乎是我想要的，但不起作用.我还尝试过这个:

I stumbled across df['environment'] = df['environment].fillna('RD') which replaces every NaN (which is not what I am looking for), pd.isnull(df['environment']) which is detecting missing values and np.where(df['environment'], x,y) which seems to be what I want but isn't working. Furthermore did I try this:

import pandas as pd

for env in df['environment']:
    if pd.isnull(env) and df['event'] == 'add_rd':
        env = 'RD'

缺少索引或某种迭代器来访问 event 列中的等效值.
我试过这个:

The indexes are missing or some kind of iterator to access the equivalent value in the event column.
And I tried this:

df['environment'] = np.where(pd.isnull(df['environment']), df['environment'] = 'RD', df['environment'])

SyntaxError: keyword can't be an expression

这显然没有用.

我查看了几个问题，但无法以答案中的建议为基础.布莱克的问题 西蒙的问题a> szli 的问题 Jan Willems Tulp 的问题

I took a look at several questions but couldn't build on the suggestions in the answers. Black's question Simon's question szli's question Jan Willems Tulp's question

那么，如何根据另一列的值替换一列中的值?

So, how do I replace a value in a column based on another columns values?

推荐答案

现在我的目标是针对事件列中的每个 add_rd，关联的环境列中的 NaN 值应替换为字符串研发.

Now my goal is for each add_rd in the event column, the associated NaN-value in the environment column should be replaced with a string RD.

根据@Zero 的评论，使用 pd.DataFrame.loc 和布尔索引:

As per @Zero's comment, use pd.DataFrame.loc and Boolean indexing:

df.loc[df['event'].eq('add_rd') & df['environment'].isnull(), 'environment'] = 'RD'

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