| pd.Series(list of values) |
creste a list with default integer index, you can access value by using s[index] |
| pd.read_csv("name of csv") |
|
| pd.concat((df1, df3), axis= ,join = "" sort) |
concatenate dataframes |
|
|
| df = pd.DataFrame() |
|
| df.info() |
|
| df.index |
*no brackets, return a list of index |
| df.empty |
return a boolean, True if empty |
| df.ndim |
return dimension count |
| df.shape |
|
| df.size |
get count of elements |
| df.at([index, column]) |
access single element |
| df.reset_index() |
|
| df.append() |
smilar to pd.concat |
| df.query('condition') |
such as 'a>100 and 'b<20' |
| df.to_html() |
|
| df.max() |
default axis=0, return maximum of every column |
| df.max().max() |
maximum of the table |
| df.mean() |
|
| df.mean().mean() |
|
| df.fillna() |
|
| df.axes |
axes info |
| df.columns |
columns name, can be rewriten |
| df.dtype |
|
| df.iterrows() |
iterate over rows |
| df.rename() |
rename the column name |
| df.select_dtype(include='typename') |
select data by datatype |
| df.sort_values() |
sort by column name |
| df.sort_index() |
sort by index |
| df.drop() |
delete columns |
| df.set_index() |
set certain column as index |
| df.reindex() |
change order of columns |
| df.replace() |
replace values |
| df.loc()/df.iloc() |
|
| df.append() |
add rows |
| df.head() |
get first n rows |
| df.to_numpy() |
to numpy array |