對於指標值的變化順序由frequency
使用sort_index
:
df = df.sort_index()
print (df)
100MHz_Dif0 102MHz_Dif0 100MHz_Dif1 102MHz_Dif1
Frequency
90000000.0 -70.209000 -65.174004 -66.063004 -66.490997
90033330.0 -70.628998 -65.196999 -66.339996 -66.461998
90066670.0 -70.405998 -65.761002 -65.432999 -65.549004
90100000.0 -70.524002 -65.552002 -66.038002 -65.887001
90133330.0 -70.746002 -65.658997 -65.086998 -65.390999
90166670.0 -70.884003 -66.209999 -64.887001 -65.397003
90200000.0 -70.752998 -66.019997 -65.308998 -66.571999
90233330.0 -70.447998 -65.858002 -65.500000 -65.028999
90266670.0 -70.452003 -65.832001 -66.032997 -65.005997
90300000.0 -71.219002 -65.739998 -65.961998 -65.986000
90333330.0 -71.095001 -65.820999 -67.112999 -65.977997
90366670.0 -70.834000 -65.926003 -66.348000 -65.568001
而對於排序列:
df = df.sort_index(axis=1)
print (df)
100MHz_Dif0 100MHz_Dif1 102MHz_Dif0 102MHz_Dif1
Frequency
90000000.0 -70.209000 -66.063004 -65.174004 -66.490997
90033330.0 -70.628998 -66.339996 -65.196999 -66.461998
90066670.0 -70.405998 -65.432999 -65.761002 -65.549004
90100000.0 -70.524002 -66.038002 -65.552002 -65.887001
90133330.0 -70.746002 -65.086998 -65.658997 -65.390999
90166670.0 -70.884003 -64.887001 -66.209999 -65.397003
90200000.0 -70.752998 -65.308998 -66.019997 -66.571999
90233330.0 -70.447998 -65.500000 -65.858002 -65.028999
90266670.0 -70.452003 -66.032997 -65.832001 -65.005997
90300000.0 -71.219002 -65.961998 -65.739998 -65.986000
90333330.0 -71.095001 -67.112999 -65.820999 -65.977997
90366670.0 -70.834000 -66.348000 -65.926003 -65.568001
而對於各種各樣的都 - index
和columns
:
df = df.sort_index(axis=1).sort_index()
print (df)
100MHz_Dif0 100MHz_Dif1 102MHz_Dif0 102MHz_Dif1
Frequency
90000000.0 -70.209000 -66.063004 -65.174004 -66.490997
90033330.0 -70.628998 -66.339996 -65.196999 -66.461998
90066670.0 -70.405998 -65.432999 -65.761002 -65.549004
90100000.0 -70.524002 -66.038002 -65.552002 -65.887001
90133330.0 -70.746002 -65.086998 -65.658997 -65.390999
90166670.0 -70.884003 -64.887001 -66.209999 -65.397003
90200000.0 -70.752998 -65.308998 -66.019997 -66.571999
90233330.0 -70.447998 -65.500000 -65.858002 -65.028999
90266670.0 -70.452003 -66.032997 -65.832001 -65.005997
90300000.0 -71.219002 -65.961998 -65.739998 -65.986000
90333330.0 -71.095001 -67.112999 -65.820999 -65.977997
90366670.0 -70.834000 -66.348000 -65.926003 -65.568001
可能重複:HTTPS ://stackoverflow.com/questions/13148429/how-to-change-the-order-of-dataframe-columns/39237712 –
做你是指列或行?你能提供你的預期輸出的樣子嗎?目前,我很困惑。我提供了一種移動行的方法。但是,我很不清楚你的意思是按頻率排序。你在你的頻率索引(已經排序)和頻率在你的列標題。 – piRSquared
對不起,我想要的是像9.003333e + 07這行從第二行移動到第一行並保持其他行相同。這只是一個例子,我可以對頻率進行排序,並將我想要的頻率移動到頂端行。 – Dogod