[英]Special Sorting columns dataframes
I have the dataframre below.我有下面的数据框。
d = {'id': ['x1', 'x2','x3','x4','x5','x6','x7'],'t1': [3,11,4,4,10,16,8],'t2':[20,14,4,15,22,11,4],
't3':[14,2,12,18,16,16,11]}
df = pd.DataFrame(data=d)
I want to do add column that contains the sort on t1 then if for two lines we have t1 equal then we can have a look on t2 and do the same thing.我想在 t1 上添加包含排序的列,然后如果两行的 t1 相等,那么我们可以查看 t2 并做同样的事情。 My column will contain.
我的专栏将包含。
df['calculated'] =[7,2,6,5,3,1,4]
My dataframe expected will be:我的 dataframe 预计将是:
d = {'id': ['x1', 'x2','x3','x4','x5','x6','x7'],'t1': [3,11,4,4,10,16,8],'t2':[20,14,4,15,22,11,4],
't3':[14,2,12,18,16,16,11],'calculated':[7,2,6,5,3,1,4]}
df = pd.DataFrame(data=d)
Use DataFrame.sort_values
by all columns for test if equal and create new column eg by DataFrame.assign
:通过所有列使用
DataFrame.sort_values
测试是否相等并创建新列,例如通过DataFrame.assign
:
df1 = df.sort_values(['t1','t2','t3'], ascending=False).assign(new=range(1, len(df) + 1))
print (df1)
id t1 t2 t3 calculated new
5 x6 16 11 16 1 1
1 x2 11 14 2 2 2
4 x5 10 22 16 3 3
6 x7 8 4 11 4 4
3 x4 4 15 18 5 5
2 x3 4 4 12 6 6
0 x1 3 20 14 7 7
Last if necessary original index add DataFrame.sort_index
:最后如果需要原始索引添加
DataFrame.sort_index
:
df1 = df1.sort_index()
print (df1)
id t1 t2 t3 calculated new
0 x1 3 20 14 7 7
1 x2 11 14 2 2 2
2 x3 4 4 12 6 6
3 x4 4 15 18 5 5
4 x5 10 22 16 3 3
5 x6 16 11 16 1 1
6 x7 8 4 11 4 4
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