pandas
DESCRIPTION
Attributes
DataFrame.index
DataFrame.columns
Methods
method | DataFrame | Series | Index | note |
---|---|---|---|---|
describe | O | O | X | |
head | O | O | X | |
unique | X | O | O | |
value_counts | O | O | O | Return a Series containing counts of unique rows |
sort_values | O | O | O | by values (along either axis) |
sort_index | O | O | X | by labels (along an axis) |
isnull | O | O | O | |
notnull | O | O | O | |
astype | O | O | O | |
to_numpy | O | O | O | convert to NumPy array : values() 대체 |
argmax | X | O | O | Return row integer position -> iloc[] |
idxmax | O | O | X | Return label -> loc[] |
isin | O | O | O | 완전 일치 -> boolean_mask df.isin(values) : df 값들이 values 중에 있는지 |
str.contains | X | O | X | 문자열 부분 일치(포함) -> boolean_mask Series.str.contains(pat) : pat 패턴이 Series 값에서 나타는지 |
str.split | X | O | X | -> Series, Index, DataFrame or MultiIndex of splitted str list |
str.startswith | X | O | X | -> Series or Index of bool (boolean_mask) |
apply | O | O | X | ★apply a function along on axis(DataFrame)/values(Series) comparison : apply, applymap, map |
applymap | O | X | ★apply a function elementwise | |
map | X | O | O | ★substitute each value with another value(elementwise) |
sum | O | O | X | True=1 / False=0 |
iterrows | O | X | X | Iterate over DataFrame rows as (index, Series) pairs. |
Table of contents
- 01 Creating, Reading, Writing
- 02 Indexing, Selecting
- 03 Editing Dataframe
- 04 Relabeling Naming
- 05 Grouping Sorting
- 06 Combining
- 07 Missing Values