change column order dataframe python
# create a dataframe
df = pd.DataFrame({'B':[1,2],'A':[0,0],'C':[1,1]})
# reorder columns as ['A','B','C']
df = df.reindex(columns = ['A','B','C'])
change column order dataframe python
# create a dataframe
df = pd.DataFrame({'B':[1,2],'A':[0,0],'C':[1,1]})
# reorder columns as ['A','B','C']
df = df.reindex(columns = ['A','B','C'])
change column order pandas
# Want to change column3 to show up first
df = pd.Dataframe({
"column1":(1,2,3),
"column2":(4,5,6),
"column3":(7,8,9)
}
# From all solutions I could find, this seems to be the best performance wise:
col = df.pop(col_name)
df.insert(0, col.name, col)# <- works in place and returns None (at least for me)
pandas change column order
frame = frame[['column I want first', 'column I want second'...etc.]]
python pandas change column order
In [39]: df
Out[39]:
0 1 2 3 4 mean
0 0.172742 0.915661 0.043387 0.712833 0.190717 1
1 0.128186 0.424771 0.590779 0.771080 0.617472 1
2 0.125709 0.085894 0.989798 0.829491 0.155563 1
3 0.742578 0.104061 0.299708 0.616751 0.951802 1
4 0.721118 0.528156 0.421360 0.105886 0.322311 1
5 0.900878 0.082047 0.224656 0.195162 0.736652 1
6 0.897832 0.558108 0.318016 0.586563 0.507564 1
7 0.027178 0.375183 0.930248 0.921786 0.337060 1
8 0.763028 0.182905 0.931756 0.110675 0.423398 1
9 0.848996 0.310562 0.140873 0.304561 0.417808 1
In [40]: df = df[['mean', 4,3,2,1]]
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