python 판다스(pandas) DataFrame 셀 cells 작업

DataFrame 셀 작업

 

행 및 열 레이블로 셀 선택

value = df.at['row', 'col']
value = df.loc['row', 'col']
value = df['col'].at['row']

행 및 열 레이블로 셀 설정

df.at['row', 'col'] = value
df.loc['row', 'col'] = value
df['col'].at['row'] = value

라벨 선택 및 자르기

df = df.loc['row1':'row3', 'col1':'col3']

라벨로 단면 설정

df.loc['A':'C', 'col1':'col3'] = np.nan
df.loc[1:2,'col1':'col2']=np.zeros((2,2))
df.loc[1:2,'A':'C']=othr.loc[1:2,'A':'C']

정수 위치로 셀 선택

value = df.iat[9, 3] # [row, col]
value = df.iloc[0, 0] # [row, col]
value = df.iloc[len(df)-1, len(df.columns)-1]

int 위치로 셀 범위 선택

df = df.iloc[2:4, 2:4] # subset of the df
df = df.iloc[:5, :5] # top left corner
s = df.iloc[5, :] # return row as Series
df = df.iloc[5:6, :] # returns row as row

정수 위치로 셀 설정

df.iloc[0, 0] = value # [row, col]
df.iat[7, 8] = value

정수 위치로 셀 범위 설정

df.iloc[0:3, 0:5] = value
df.iloc[1:3, 1:4] = np.ones((2, 3))
df.iloc[1:3, 1:4] = np.zeros((2, 3))
df.iloc[1:3, 1:4] = np.array([[1, 1, 1],
 				[2, 2, 2]])

혼합 라벨 및 정수 위치 인덱싱을 위한 .ix

value = df.ix[5, 'col1']
df = df.ix[1:5, 'col1':'col3']

 

 

참고 : https://www.geeksforgeeks.org/pandas-cheat-sheet

Pandas Cheat Sheet for Data Science in Python