根据特定条件在 DataFrame 中插入行
Insert rows within a DataFrame, based on certain conditions
我有一个数据框，'df' 我想根据 df 本身的条件插入行。每个 'ID' 值都必须有一个对应于两种饮品类型（啤酒和葡萄酒）的条目。我想说的是，如果任何 ID 条目没有啤酒类型，例如，添加 DrinkType 等于 Beer 和 Drink 等于 'Not Stated' 的行。类似地，如果 ID 值指定了 Beer 而不是 Wine，则在 Drink Type 和 Drink 下添加 Wine 等于 'Not Stated' 的行。我希望 df 看起来像 df1。
df:
ID DrinkType Drink
130 Beer Fosters
130 Wine Rose
130 Beer Budweiser
102 Beer Fosters
120 Wine Pinot Grigot
120 Beer Budweiser
99 Wine Coke
75 Beer Carling
75 Beer Fosters
df1:
ID DrinkType Drink
130 Beer Fosters
130 Wine Rose
130 Beer Budweiser
102 Beer Fosters
102 Wine Not Stated
120 Wine Pinot Grigot
120 Beer Budweiser
99 Wine Coke
99 Beer Not Stated
75 Beer Carling
75 Beer Fosters
75 Wine Not Stated
在特定索引处的数据框中插入行的函数
def Insert_row_(row_number, df, row_value):
#Slice the upper half of the dataframe
df1 = df[0:row_number]
# Store the result of lower half of the dataframe
df2 = df[row_number:]
# Inser the row in the upper half dataframe
df1.loc[row_number]=row_value
# Concat the two dataframes
df_result = pd.concat([df1, df2])
# Reassign the index labels
df_result.index = [*range(df_result.shape[0])]
# Return the updated dataframe
return df_result
让我们创建一个要插入的行
index = 2
item_insert = ['Beer','NotStated']
if row_number > df.index.max()+1:
df[index]=row_value
else:
# Let's call the function and insert the row
# at the second position
df = Insert_row_(2, df, row_value)
print(df)
最后插入任意行
找到当前数据帧的最大索引
df[s]=rowvalue or we can use pd.concat(df,df1)
我有一个数据框，'df' 我想根据 df 本身的条件插入行。每个 'ID' 值都必须有一个对应于两种饮品类型（啤酒和葡萄酒）的条目。我想说的是，如果任何 ID 条目没有啤酒类型，例如，添加 DrinkType 等于 Beer 和 Drink 等于 'Not Stated' 的行。类似地，如果 ID 值指定了 Beer 而不是 Wine，则在 Drink Type 和 Drink 下添加 Wine 等于 'Not Stated' 的行。我希望 df 看起来像 df1。
df:
ID DrinkType Drink
130 Beer Fosters
130 Wine Rose
130 Beer Budweiser
102 Beer Fosters
120 Wine Pinot Grigot
120 Beer Budweiser
99 Wine Coke
75 Beer Carling
75 Beer Fosters
df1:
ID DrinkType Drink
130 Beer Fosters
130 Wine Rose
130 Beer Budweiser
102 Beer Fosters
102 Wine Not Stated
120 Wine Pinot Grigot
120 Beer Budweiser
99 Wine Coke
99 Beer Not Stated
75 Beer Carling
75 Beer Fosters
75 Wine Not Stated
在特定索引处的数据框中插入行的函数
def Insert_row_(row_number, df, row_value):
#Slice the upper half of the dataframe
df1 = df[0:row_number]
# Store the result of lower half of the dataframe
df2 = df[row_number:]
# Inser the row in the upper half dataframe
df1.loc[row_number]=row_value
# Concat the two dataframes
df_result = pd.concat([df1, df2])
# Reassign the index labels
df_result.index = [*range(df_result.shape[0])]
# Return the updated dataframe
return df_result
让我们创建一个要插入的行
index = 2
item_insert = ['Beer','NotStated']
if row_number > df.index.max()+1:
df[index]=row_value
else:
# Let's call the function and insert the row
# at the second position
df = Insert_row_(2, df, row_value)
print(df)
最后插入任意行
找到当前数据帧的最大索引
df[s]=rowvalue or we can use pd.concat(df,df1)