Python program to replace all values in a column, based on condition# Importing pandas package import pandas as pd # creating a dictionary of student marks d = { "Players":['Sachin','Ganguly','Dravid','Yuvraj','Dhoni','Kohli'], "Format":['ODI','ODI','ODI','ODI','ODI','ODI']...
df=pd.DataFrame(student) # Applying the condition df['gender'].mask(df['gender']=='female',0,inplace=True) # Try this too #df['math score'].mask(df['math score'] >=60 ,'good', inplace=True) 输出: 注:本文由VeryToolz翻译自How to Replace Values in Column Based on Condition in ...
如何在Pandas中根据条件替换列中的值|极客教程 https://geek-docs.com/pandas/pandas-dataframe/how-to-replace-values-in-column-based-on-condition-in-pandas.html Pandas的掩蔽函数是为了用一个条件替换任何行或列的值。现在我们使用这个屏蔽条件,将性别栏中所有的 “女性 “改为0。 语法: df[‘column_name...
Related:You can replace the Pandas values based on condition. 1. replace() Syntax Below is the syntax of the replace() method. This is also used toreplace the substringin the column. # Syntax of replace() methodDataFrame.replace(to_replace=None,value=None,inplace=False,limit=None,regex=Fa...
Pandas Replace Values based on Condition Pandas Replace NaN with Blank/Empty String Pandas Rename Index Values of DataFrame Pandas Series.replace() – Replace Values How to Replace String in pandas DataFrame pandas DataFrame replace() – by Examples ...
# Update valuesina column based on a condition df.iloc[df['Order Quantity']>3,15]='greater than 3'# condition=df['Order Quantity']>3df.iloc[condition,15]='greater than 3' replace():用新值替换DataFrame中的特定值。df.['column_name'].replace(old_value, new_value, inplace=True) ...
Replace Values Based on a Condition Remove Wrong Values Replace Individual Values We can see that the value F for Gender column is an obvious mistake. Let's replace F with M to rectify the error. import pandas as pd # create dataframe data = { 'Name': ['John', 'Michael', 'Tom', ...
# Update values in a column based on a condition df.iloc[df['Order Quantity'] > 3, 15] = 'greater than 3' # condition = df['Order Quantity'] > 3 df.iloc[condition, 15] = 'greater than 3' replace():用新值替换DataFrame中的特定值。df.['column_name'].replace(old_value, new_va...
# Update values in a column based on a condition df.iloc[df['Order Quantity'] > 3, 15] = 'greater than 3' # condition = df['Order Quantity'] > 3 df.iloc[condition, 15] = 'greater than 3' replace():用新值替换DataFrame中的特定值。df.['column_name'].replace(old_value, new_va...
# Update valuesina column based on a condition df.iloc[df['Order Quantity']>3,15]='greater than 3'# condition=df['Order Quantity']>3df.iloc[condition,15]='greater than 3' 1. 2. 3. 4. 5. 6. replace():用新值替换DataFrame中的特定值。df.['column_name'].replace(old_value, new...