Pandas – basic operation of dataframe

We learned in the last sectionSeriesThe basic operations of structure addition, deletion, modification and query are mastered in this sectionDataFrameIt will be very easy to add, delete, modify and check~

First, let’s construct aDataFrame ：

data = [[1,2,3], [4,5,6], [7,8,9]]
index = ['a', 'b', 'c']
columns = ['A', 'B', 'C']
df = pd.DataFrame(data=data, index=index, columns=columns)
df

check

Query specified column:

>> df['A']
a    1
b    4
c    7
Name: A, dtype: int64
>> df[['A','C']]
    A   C
a   1   3
b   4   6
c   7   9

uselocandilocQuery the specified row:

>> df.loc['a']
A    1
B    2
C    3
Name: a, dtype: int64
>> df.iloc[0]
A    1
B    2
C    3
Name: a, dtype: int64
>> df.loc['a':'b']
    A   B   C
a   1   2   3
b   4   5   6
>> df.iloc[:2]
    A   B   C
a   1   2   3
b   4   5   6

In addition,ilocandlocYou can also receive a coordinate and queryDataFrameSpecified value or area of:

>> df.loc['b','B']
5
>> df.loc['a':'b',['A','C']]
    A   C
a   1   3
b   4   6

Finally, there are frequently used Boolean indexes:

>> df[[True, False, True]]
    A   B   C
a   1   2   3
c   7   8   9

change

Modify the specified value:

>> df.loc['a', 'A']
1
>> df.loc['a', 'A'] = 1000
>> df

Modify index and column names:

>> df.index = ['aa','bb','cc']
>> df.columns = ['AA','BB','CC']
>> df

increase

Add a line:

>> df.loc['dd'] = [0,0,0]
>> df

Add multiple lines of content (splicing two vertically)DataFrame）First, construct a new dataframedf2 ：

>> df2 = pd.DataFrame(data=[[10,10,10], [100, 100, 100]], 
                      index=['dd', 'ee'], 
                      columns=['AA', 'BB', 'CC'])
>> df2

Splice two dataframes:

>> df3 = pd.concat([df, df2])
>> df3

pd.concatOnly simple splicing is done, and even repeated indexes will not be overwritten:

>> df3.loc['dd']
    AA  BB  CC
dd  0   0   0
dd  10  10  10

Usually, we useignore_index=TrueTo reproduce the digital index:

>> df3 = pd.concat([df, df2], ignore_index=True)
>> df3

bydf2Add a columnDD ：

>> df2['DD'] = [1000, 1000]
>> df2

What about adding multiple columns? We still use the samepd.concat, but set the parameter toaxis=1。 Let’s construct a dataframe with two rows and two columnsdf4 ：

>> df4 = pd.DataFrame([[1,2],[3,4]], index=['dd','ee'], columns=['E','F'])
>> df4
    E   F
dd  1   2
ee  3   4

Splicingdf2Anddf4 ：

>> df5 = pd.concat([df2,df4], axis=1)
>> df5

Delete

Delete the abovedf5MediumEColumn sumFColumns:

>> del df5['E']
>> del df5['F']
>> df5

When deleting multiple columns, you can also usedropMethod, but specifyaxis=1 ：

>> df5.drop(['CC','DD'], axis=1, inplace=True)
>> df5

You can also usedropMethod to delete multiple rows. The default parameter is used when deleting rowsaxis=0You can:

>> df5.drop(['dd'], inplace=True)
>> df5