| Function |
Description |
| dataframe.head(n) |
to show the first n rows of dataframe || else top 5 |
| dataframe.tail(n) |
to show the bottom n rows of dataframe || else bottom 5 |
| dataframe.shape |
size of dataframe (rows, columns) |
| dataframe.dtypes() |
to check data types |
| dataframe.describe() |
returns a statistical summary |
| dataframe.describe(include="all") |
returns a statistical summary of all including objects |
| dataframe.info() |
provides a concise summary of all your dataframe |
| dataframe.astype() |
to convert data types |
| dataframe.columns.values |
to get a array of column headers from |
| dataframe.index.values |
to get a array of index |
| Command |
Description |
| dataframe.set_index("key", inplace=True) |
changes the index of the dataframe to given column "key" |
| dataframe.reset_index() |
resets the index of the dataframe |
| dataframe.dropna(axis=0) |
drops the entire row if found empty |
| dataframe.dropna(axis=1) |
drops the entier column if found empty |
| dataframe.dropna( [keys] ,inplace=True) |
applies changes to the actual dataframe itself |
| dataframe.replace( missing_value, new_value ) |
replace value of one to another in dataframe |
| dataframe.rename( columns={prevkey:newkey} ) |
rename columns of the dataframe |
| dataframe.sum( axis=1 ) |
returnsm sum of the row |
| dataframe["key"].std() |
returns the standard deviation |
| dataframe["key"].mean() |
returns the mean of the column |
| pd.get_dummies(df[column]) |
Convert categorical variables to dummy variables (0 or 1) [One - hot encoding] |
| dataframe.groupby([column, column]) |
Group dataframe based on column |
| dataframe[column].agg('function') |
Perform an operation in a particular coulmn |