Pandas - DataFrame Reference
All properties and methods of the DataFrame object, with explanations and examples:
| Property/Method | Description |
|---|---|
| abs() | Return a DataFrame with the absolute value of each value |
| add() | Adds the values of a DataFrame with the specified value(s) |
| add_prefix() | Prefix all labels |
| add_suffix() | Suffix all labels |
| agg() | Apply a function or a function name to one of the axis of the DataFrame |
| aggregate() | Apply a function or a function name to one of the axis of the DataFrame |
| align() | Aligns two DataFrames with a specified join method |
| all() | Return True if all values in the DataFrame are True, otherwise False |
| any() | Returns True if any of the values in the DataFrame are True, otherwise False |
| append() | Append new columns |
| applymap() | Execute a function for each element in the DataFrame |
| apply() | Apply a function to one of the axis of the DataFrame |
| assign() | Assign new columns |
| astype() | Convert the DataFrame into a specified dtype |
| at | Get or set the value of the item with the specified label |
| axes | Returns the labels of the rows and the columns of the DataFrame |
| bfill() | Replaces NULL values with the value from the next row |
| bool() | Returns the Boolean value of the DataFrame |
| columns | Returns the column labels of the DataFrame |
| combine() | Compare the values in two DataFrames, and let a function decide which values to keep |
| combine_first() | Compare two DataFrames, and if the first DataFrame has a NULL value, it will be filled with the respective value from the second DataFrame |
| compare() | Compare two DataFrames and return the differences |
| convert_dtypes() | Converts the columns in the DataFrame into new dtypes |
| corr() | Find the correlation (relationship) between each column |
| count() | Returns the number of not empty cells for each column/row |
| cov() | Find the covariance of the columns |
| copy() | Returns a copy of the DataFrame |
| cummax() | Calculate the cumulative maximum values of the DataFrame |
| cummin() | Calculate the cumulative minmum values of the DataFrame |
| cumprod() | Calculate the cumulative product over the DataFrame |
| cumsum() | Calculate the cumulative sum over the DataFrame |
| describe() | Returns a description summary for each column in the DataFrame |
| diff() | Calculate the difference between a value and the value of the same column in the previous row |
| div() | Divides the values of a DataFrame with the specified value(s) |
| dot() | Multiplies the values of a DataFrame with values from another array-like object, and add the result |
| drop() | Drops the specified rows/columns from the DataFrame |
| drop_duplicates() | Drops duplicate values from the DataFrame |
| droplevel() | Drops the specified index/column(s) |
| dropna() | Drops all rows that contains NULL values |
| dtypes | Returns the dtypes of the columns of the DataFrame |
| duplicated() | Returns True for duplicated rows, otherwise False |
| empty | Returns True if the DataFrame is empty, otherwise False |
| eq() | Returns True for values that are equal to the specified value(s), otherwise False |
| equals() | Returns True if two DataFrames are equal, otherwise False |
| eval | Evaluate a specified string |
| explode() | Converts each element into a row |
| ffill() | Replaces NULL values with the value from the previous row |
| fillna() | Replaces NULL values with the specified value |
| filter() | Filter the DataFrame according to the specified filter |
| first() | Returns the first rows of a specified date selection |
| floordiv() | Divides the values of a DataFrame with the specified value(s), and floor the values |
| ge() | Returns True for values greater than, or equal to the specified value(s), otherwise False |
| get() | Returns the item of the specified key |
| groupby() | Groups the rows/columns into specified groups |
| gt() | Returns True for values greater than the specified value(s), otherwise False |
| head() | Returns the header row and the first 10 rows, or the specified number of rows |
| iat | Get or set the value of the item in the specified position |
| idxmax() | Returns the label of the max value in the specified axis |
| idxmin() | Returns the label of the min value in the specified axis |
| iloc | Get or set the values of a group of elements in the specified positions |
| index | Returns the row labels of the DataFrame |
| infer_objects() | Change the dtype of the columns in the DataFrame |
| info() | Prints information about the DataFrame |
| insert() | Insert a column in the DataFrame |
| interpolate() | Replaces not-a-number values with the interpolated method |
| isin() | Returns True if each elements in the DataFrame is in the specified value |
| isna() | Finds not-a-number values |
| isnull() | Finds NULL values |
| items() | Iterate over the columns of the DataFrame |
| iteritems() | Iterate over the columns of the DataFrame |
| iterrows() | Iterate over the rows of the DataFrame |
| itertuples() | Iterate over the rows as named tuples |
| join() | Join columns of another DataFrame |
| last() | Returns the last rows of a specified date selection |
| le() | Returns True for values less than, or equal to the specified value(s), otherwise False |
| loc | Get or set the value of a group of elements specified using their labels |
| lt() | Returns True for values less than the specified value(s), otherwise False |
| keys() | Returns the keys of the info axis |
| kurtosis() | Returns the kurtosis of the values in the specified axis |
| mask() | Replace all values where the specified condition is True |
| max() | Return the max of the values in the specified axis |
| mean() | Return the mean of the values in the specified axis |
| median() | Return the median of the values in the specified axis |
| melt() | Reshape the DataFrame from a wide table to a long table |
| memory_usage() | Returns the memory usage of each column |
| merge() | Merge DataFrame objects |
| min() | Returns the min of the values in the specified axis |
| mod() | Modules (find the remainder) of the values of a DataFrame |
| mode() | Returns the mode of the values in the specified axis |
| mul() | Multiplies the values of a DataFrame with the specified value(s) |
| ndim | Returns the number of dimensions of the DataFrame |
| ne() | Returns True for values that are not equal to the specified value(s), otherwise False |
| nlargest() | Sort the DataFrame by the specified columns, descending, and return the specified number of rows |
| notna() | Finds values that are not not-a-number |
| notnull() | Finds values that are not NULL |
| nsmallest() | Sort the DataFrame by the specified columns, ascending, and return the specified number of rows |
| nunique() | Returns the number of unique values in the specified axis |
| pct_change() | Returns the percentage change between the previous and the current value |
| pipe() | Apply a function to the DataFrame |
| pivot() | Re-shape the DataFrame |
| pivot_table() | Create a spreadsheet pivot table as a DataFrame |
| pop() | Removes an element from the DataFrame |
| pow() | Raise the values of one DataFrame to the values of another DataFrame |
| prod() | Returns the product of all values in the specified axis |
| product() | Returns the product of the values in the specified axis |
| quantile() | Returns the values at the specified quantile of the specified axis |
| query() | Query the DataFrame |
| radd() | Reverse-adds the values of one DataFrame with the values of another DataFrame |
| rdiv() | Reverse-divides the values of one DataFrame with the values of another DataFrame |
| reindex() | Change the labels of the DataFrame |
| reindex_like() | ?? |
| rename() | Change the labels of the axes |
| rename_axis() | Change the name of the axis |
| reorder_levels() | Re-order the index levels |
| replace() | Replace the specified values |
| reset_index() | Reset the index |
| rfloordiv() | Reverse-divides the values of one DataFrame with the values of another DataFrame |
| rmod() | Reverse-modules the values of one DataFrame to the values of another DataFrame |
| rmul() | Reverse-multiplies the values of one DataFrame with the values of another DataFrame |
| round() | Returns a DataFrame with all values rounded into the specified format |
| rpow() | Reverse-raises the values of one DataFrame up to the values of another DataFrame |
| rsub() | Reverse-subtracts the values of one DataFrame to the values of another DataFrame |
| rtruediv() | Reverse-divides the values of one DataFrame with the values of another DataFrame |
| sample() | Returns a random selection elements |
| sem() | Returns the standard error of the mean in the specified axis |
| select_dtypes() | Returns a DataFrame with columns of selected data types |
| shape | Returns the number of rows and columns of the DataFrame |
| set_axis() | Sets the index of the specified axis |
| set_flags() | Returns a new DataFrame with the specified flags |
| set_index() | Set the Index of the DataFrame |
| size | Returns the number of elements in the DataFrame |
| skew() | Returns the skew of the values in the specified axis |
| sort_index() | Sorts the DataFrame according to the labels |
| sort_values() | Sorts the DataFrame according to the values |
| squeeze() | Converts a single column DataFrame into a Series |
| stack() | Reshape the DataFrame from a wide table to a long table |
| std() | Returns the standard deviation of the values in the specified axis |
| sum() | Returns the sum of the values in the specified axis |
| sub() | Subtracts the values of a DataFrame with the specified value(s) |
| swaplevel() | Swaps the two specified levels |
| T | Turns rows into columns and columns into rows |
| tail() | Returns the headers and the last rows |
| take() | Returns the specified elements |
| to_xarray() | Returns an xarray object |
| transform() | Execute a function for each value in the DataFrame |
| transpose() | Turns rows into columns and columns into rows |
| truediv() | Divides the values of a DataFrame with the specified value(s) |
| truncate() | Removes elements outside of a specified set of values |
| update() | Update one DataFrame with the values from another DataFrame |
| value_counts() | Returns the number of unique rows |
| values | Returns the DataFrame as a NumPy array |
| var() | Returns the variance of the values in the specified axis |
| where() | Replace all values where the specified condition is False |
| xs() | Returns the cross-section of the DataFrame |
| __iter__() | Returns an iterator of the info axes |
