pandas 从现有数据帧 python 中选择特定行创建一个新的数据帧
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create a new dataframe from selecting specific rows from existing dataframe python
提问by Shubham R
i have a table in my pandas dataframe. df
我的Pandas数据框中有一张表。df
id count price
1 2 100
2 7 25
3 3 720
4 7 221
5 8 212
6 2 200
i want to create a new dataframe(df2) from this, selecting rows where count is 2 and price is 100,and count is 7 and price is 221
我想从中创建一个新的数据框（df2），选择计数为 2，价格为 100，计数为 7，价格为 221 的行
my output should be df2 =
我的输出应该是 df2 =
id count price
1 2 100
4 7 221
i am trying using df[df['count'] == '2' & df['price'] == '100']
我正在尝试使用 df[df['count'] == '2' & df['price'] == '100']
but getting error
但得到错误
TypeError: cannot compare a dtyped [object] array with a scalar of type [bool]
回答by jezrael
You nedd add ()because &has higher precedence than ==:
你 nedd add()因为&具有更高的优先级==：
df3 = df[(df['count'] == '2') & (df['price'] == '100')]
print (df3)
id count price
0 1 2 100
If need check multiple values use isin:
如果需要检查多个值，请使用isin：
df4 = df[(df['count'].isin(['2','7'])) & (df['price'].isin(['100', '221']))]
print (df4)
id count price
0 1 2 100
3 4 7 221
But if check numeric, use:
但如果检查数字，请使用：
df3 = df[(df['count'] == 2) & (df['price'] == 100)]
print (df3)
df4 = df[(df['count'].isin([2,7])) & (df['price'].isin([100, 221]))]
print (df4)
