Accessing.md

Access Data

Index

• Index object is an immutable array.
• There are two types of index in a DataFrame row index and column index
• Both indexes starts from 0, allows to access a row or column using an index position or label name.

# First row and first column:
df.iloc[0, 0]

Access Data

Method	Access	Example
.at[]	Access scalar value + Label based location	df.at[1,'Country'] or df['City'].at[1]
.iat[]	Access scalar value + Integer based location	df.iat[1,3] or df['City'].iat[1]
.loc[]	Access record or field + Label based location	df.loc[0,'City'] or df['City'].loc[1]
.iloc[]	Access record or field + Integer based location	df.iloc[0,1] or df['City'].iloc[1]

Access scalar value

DataFrame.at[] : Label based location

# DataFrame:
print(df.at[1, 'Country'])

# Series:
print(df['Country'].at[1])

DataFrame.iat[] : Integer based location

print(df.iat[1, 3])

Access scalar value or entire row or column

DataFrame.loc[] : Label based location

# DataFrame.loc[]
print(df.loc[0, 'City'])

# Subset of DataFrame:
print(df.loc[[1, 2, 3], ['City', 'State', 'Country']])

# Slicing DataFrame:
print(df.loc[1:5, 'Name':'Country'])

# DataFrame.Series.loc[]
print(df['City'].loc[1])

# Subset of DataFrame:
print(df[['City', 'State', 'Country']].loc[[1, 2, 3]])

# Slicing DataFrame:
print(df['Name':'Country'].loc[1:5])

DataFrame.iloc[] : Integer based location

# DataFrame.iloc[]
print(df.iloc[0, 1])

# Subset of DataFrame:
print(df.iloc[[1, 2, 3], [2, 4, 6]])

# Slicing DataFrame:
print(df.iloc[1:5, 1:6:2])

# DataFrame.Series.iloc[]
print(df['City'].iloc[1])

# Subset of DataFrame:
print(df[['City', 'State', 'Country']].iloc[[1, 2, 3]])

# Slicing DataFrame:
print(df['Name':'Country'].iloc[1:5])