Pandas 기본 기능

Pandas

Importing Pandas

import pandas as pd

Creating DataFrames

# From a dictionary
data = {'Column1': [1, 2, 3, 4], 'Column2': ['a', 'b', 'c', 'd']}
df = pd.DataFrame(data)

# From a CSV file
df = pd.read_csv('file_path.csv')

# From an Excel file
df = pd.read_excel('file_path.xlsx', sheet_name='Sheet1')

https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html

Intro to data structures — pandas 2.2.2 documentation

 

Viewing Data

df.head()  # 첫 5행
df.tail()  # 마지막 5행
df.sample(n=5)  # 무작위 샘플 n행
df.info()  # 데이터프레임 정보
df.describe()  # 기술 통계

https://pandas.pydata.org/pandas-docs/stable/user_guide/basics.html#viewing-data

Essential basic functionality — pandas 2.2.2 documentation

 

Selecting Data

# Column selection
df['Column1']  # 시리즈 반환
df[['Column1', 'Column2']]  # 데이터프레임 반환

# Row selection by index
df.iloc[0]  # 첫 번째 행 (integer-location based)
df.loc[0]  # 첫 번째 행 (label-based)

# Conditional selection
df[df['Column1'] > 2]  # 조건 만족하는 행 선택

https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html

Indexing and selecting data — pandas 2.2.2 documentation

 

Data Cleaning

# Handling missing values
df.dropna()  # 결측값 있는 행 삭제
df.fillna(value)  # 결측값 채우기

# Duplicates
df.drop_duplicates()  # 중복 행 제거

# Renaming columns
df.rename(columns={'OldName': 'NewName'}, inplace=True)

# Changing data types
df['Column1'] = df['Column1'].astype('int')

https://pandas.pydata.org/pandas-docs/stable/user_guide/missing_data.html

Working with missing data — pandas 2.2.2 documentation

 

Data Manipulation

# Adding a new column
df['NewColumn'] = df['Column1'] + df['Column2']

# Applying functions
df['NewColumn'] = df['Column1'].apply(lambda x: x * 2)

# Grouping data
grouped = df.groupby('Column1').sum()

# Merging DataFrames
df_merged = pd.merge(df1, df2, on='KeyColumn', how='inner')  # 'left', 'right', 'outer' 가능

https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html

Merge, join, concatenate and compare — pandas 2.2.2 documentation

 

Saving Data

df.to_csv('file_path.csv', index=False)
df.to_excel('file_path.xlsx', sheet_name='Sheet1', index=False)

https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html

IO tools (text, CSV, HDF5, …) — pandas 2.2.2 documentation

 

Useful Functions

# Sorting
df.sort_values(by='Column1', ascending=False)

# Pivot Table
pivot = df.pivot_table(index='Column1', columns='Column2', values='Column3', aggfunc='sum')

# Reset index
df.reset_index(drop=True, inplace=True)

https://pandas.pydata.org/pandas-docs/stable/user_guide/basics.html

Essential basic functionality — pandas 2.2.2 documentation

 

Time Series

# Converting to datetime
df['Date'] = pd.to_datetime(df['Date'])

# Setting index
df.set_index('Date', inplace=True)

# Resampling
df.resample('M').mean()  # 'D': day, 'W': week, 'M': month, 'Q': quarter, 'Y': year

https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html

Time series / date functionality — pandas 2.2.2 documentation

 

 

 

 

판다스 치트 시트 경로: https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf

10 minutes to pandas: https://pandas.pydata.org/docs/user_guide/10min.html