[英]Python Pandas - Replacing values of a part of data frame column based on index
I am fetching the first occurrence of a particular value in a Panda column based on its index as shown below : 我正在根据其索引在Panda列中获取特定值的首次出现,如下所示:
first_idx = df1.loc[df1.Column1.isin(['word1','word2'])].index.tolist()[0]
This will give me the index of first occurrence of either 'word1' or 'word2' 这将为我提供“ word1”或“ word2”首次出现的索引
Then I am replacing old values of the records until the determined index with new values as shown below : 然后,我要用新值替换记录的旧值,直到确定的索引为止,如下所示:
df1.head(first_idx)['Column1'].replace({'10': '5'}, inplace=True)
This will replace all '10's that are present until the first_idx of the dataframe with '5's. 这将用“ 5”替换直到数据帧的first_idx之前存在的所有“ 10”。 All the remaining '10's present after the first_idx value will not be replaced.
first_idx值之后的所有剩余的'10'将不被替换。
Now I have to replace all '10's present after the first_idx value with '3's. 现在,我必须将first_idx值之后的所有'10'替换为'3'。 I have tried the below by calculating the length of data frame and then subtracting it with the first_idx value.
我通过计算数据帧的长度,然后用first_idx值减去它,尝试了以下方法。
len(df1) # This will show the actual length / total number of records of a dataframe column.
temp = (len(df1)-first_idx)-1 # This will determine the remaining count of records barring the count of records until first_idx value.
df1.tail(temp) # This will show all records that are present after the first_idx value.
df1.tail(temp)['Column1'].replace({'10': '3'}, inplace=True)
But is there any other better / efficient / simple way to achieve the same ? 但是还有其他更好/有效/简单的方法来实现这一目标吗?
From the way you used 从您使用的方式
df1.head(first_idx)
I assume your indices are numeric. 我认为您的索引是数字。 Thus, a simple
因此,一个简单的
df1.iloc[first_idx + 1:, :]['Column1'].replace({'10': '3'}, inplace=True)
Should do. 应该做。
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