Python Pandsは列/行を選択し、追加、削除します。
一、列操作
1.1列の選択
a. 1.0
b 2.0
c 3.0
d NaN
Name:one,dtype:float 64
1.2列を増やす
Adding a new column by passing as Series:
one two three
a. 1.0 1 10.0
b 2.0 2 20.0.
c 3.0 3 30.0
d NaN 4 NaN
Adding a new column using the existing columns in DataFrame:
one two three four
a. 1.0 1 10.0 12.0
b 2.0 2 20.0. 24.0
c 3.0 3 30.0 36.0
d NaN 4 NaN NaN
1.3列(delとpop関数)を削除する
Our data frame is:
one two three
a. 1.0 1 10.0
b 2.0 2 20.0.
c 3.0 3 30.0
d NaN 4 NaN
Deleting the first column using DEL function:
two three
a. 1 10.0
b 2 20.0.
c 3 30.0
d 4 NaN
Deleting another column using POP function:
three
a. 10.0
b 20.0.
c 30.0
d NaN
POP column:
a. 1
b 2
c 3
d 4
Name:two,dtype:int 64
二、行操作
2.1行の選択
2.1.1 labelで行を選択する(loc関数)
one 2.0
two 2.0
Name:b,dtype:float 64
2.1.2シリアル番号で行を選択する(iloc関数)
one 3.0
two 3.0
Name:c,dtype:float 64
2.1.3シリアル番号で行スライスを選択する
one two
c 3.0 3
d NaN 4
2.2行を増やす(apped関数)
a. b
0 1 2
1 3 4
0 5 6
1 7 8
a. b
0 1 2
0 5 6
2.3行の削除(drop関数)
a. b
1 3 4
1 7 8
ここでは、Python Pandsについて列/行を選択し、追加し、削除操作の記事をここに紹介します。Python Pandsの行列に関連して、削除内容を追加します。以前の文章を検索したり、下記の関連記事を見たりしてください。これからも私達を応援してください。
1.1列の選択
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
print (df ['one'])
# ,
# index , ,
実行結果:a. 1.0
b 2.0
c 3.0
d NaN
Name:one,dtype:float 64
1.2列を増やす
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
# Adding a new column to an existing DataFrame object with column label by passing new series
print ("Adding a new column by passing as Series:")
df['three']=pd.Series([10,30,20],index=['a','c','b'])
print(df)
# , index ( )
print ("Adding a new column using the existing columns in DataFrame:")
df['four']=df['one']+df['two']+df['three']
print(df)
# , , NaN , NaN
実行結果:Adding a new column by passing as Series:
one two three
a. 1.0 1 10.0
b 2.0 2 20.0.
c 3.0 3 30.0
d NaN 4 NaN
Adding a new column using the existing columns in DataFrame:
one two three four
a. 1.0 1 10.0 12.0
b 2.0 2 20.0. 24.0
c 3.0 3 30.0 36.0
d NaN 4 NaN NaN
1.3列(delとpop関数)を削除する
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd']),
'three' : pd.Series([10,20,30], index=['a','b','c'])}
df = pd.DataFrame(d)
print ("Our dataframe is:")
print(df)
# del
print ("Deleting the first column using DEL function:")
del(df['one'])
print(df)
# pop
print ("Deleting another column using POP function:")
df_2=df.pop('two') # pop dataframe
print(df_2)
print(df)
実行結果:Our data frame is:
one two three
a. 1.0 1 10.0
b 2.0 2 20.0.
c 3.0 3 30.0
d NaN 4 NaN
Deleting the first column using DEL function:
two three
a. 1 10.0
b 2 20.0.
c 3 30.0
d 4 NaN
Deleting another column using POP function:
three
a. 10.0
b 20.0.
c 30.0
d NaN
POP column:
a. 1
b 2
c 3
d 4
Name:two,dtype:int 64
二、行操作
2.1行の選択
2.1.1 labelで行を選択する(loc関数)
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
print(df.loc['b']) # , , index
実行結果:one 2.0
two 2.0
Name:b,dtype:float 64
2.1.2シリアル番号で行を選択する(iloc関数)
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
print(df.iloc[2]) # 2 3
実行結果:one 3.0
two 3.0
Name:c,dtype:float 64
2.1.3シリアル番号で行スライスを選択する
d = {'one' : pd.Series([1, 2, 3], index=['a', 'b', 'c']),
'two' : pd.Series([1, 2, 3, 4], index=['a', 'b', 'c', 'd'])}
df = pd.DataFrame(d)
print(df[2:4]) # 3 4 , Python , ,
実行結果:one two
c 3.0 3
d NaN 4
2.2行を増やす(apped関数)
# append
df = pd.DataFrame([[1, 2], [3, 4]], columns = ['a','b'])
df2 = pd.DataFrame([[5, 6], [7, 8]], columns = ['a','b'])
df = df.append(df2)
print(df) # dataframe , index 0 1
print(df.loc[0]) # index 0
実行結果:a. b
0 1 2
1 3 4
0 5 6
1 7 8
a. b
0 1 2
0 5 6
2.3行の削除(drop関数)
# drop
df = pd.DataFrame([[1, 2], [3, 4]], columns = ['a','b'])
df2 = pd.DataFrame([[5, 6], [7, 8]], columns = ['a','b'])
df = df.append(df2)
df = df.drop(0) # 0, 2
print(df)
実行結果:a. b
1 3 4
1 7 8
ここでは、Python Pandsについて列/行を選択し、追加し、削除操作の記事をここに紹介します。Python Pandsの行列に関連して、削除内容を追加します。以前の文章を検索したり、下記の関連記事を見たりしてください。これからも私達を応援してください。