vDataFrame.animated

In [ ]:
vDataFrame.animated(ts: str,
                    columns: list = [],
                    by: str = "",
                    start_date: (str, datetime.datetime, datetime.date,) = "",
                    end_date: (str, datetime.datetime, datetime.date,) = "",
                    kind: str = "auto",
                    limit_over: int = 6,
                    limit: int = 1000000,
                    limit_labels: int = 6,
                    ts_steps: dict = {"window": 100, "step": 5},
                    bubble_img: dict = {"bbox": [], "img": ""},
                    fixed_xy_lim: bool = False,
                    date_in_title: bool = False,
                    date_f = None,
                    date_style_dict: dict = {},
                    interval: int = 300,
                    repeat: bool = True,
                    return_html: bool = True,
                    ax=None,
                    **style_kwds,)

Draws the animated chart.

Parameters

Name Type Optional Description
ts
str
❌
 TS (Time Series) vColumn to use to order the data. The vColumn type must be date like (date, datetime, timestamp...) or numerical.
columns
list
❌
 List of the vColumns names.
by
str
✓
 Categorical vColumn used in the partition.
start_date
str / date
✓
 Input Start Date. For example, time = '03-11-1993' will filter the data when 'ts' is lesser than November 1993 the 3rd.
end_date
str / date
✓
 Input End Date. For example, time = '03-11-1993' will filter the data when 'ts' is greater than November 1993 the 3rd.
kind
str
✓
 Animation Type.
  • auto : Pick up automatically the type.
  • bar :Animated Bar Race.
  • bubble : Animated Bubble Plot.
  • pie : Animated Pie Chart.
  • ts : Animated Time Series.
limit_over
int
✓
 Limited number of elements to consider for each category.
limit
int
✓
 Maximum number of data points to use.
limit_labels
int
✓
 [Only used when kind = 'bubble']
Maximum number of text labels to draw.
ts_steps
dict
✓
 [Only used when kind = 'ts']
dictionary including 2 keys.
  • step: number of elements used to update the time series.
  • window: size of the window used to draw the time series.
bubble_img
dict
✓
 [Only used when kind = 'bubble']
dictionary including 2 keys.
  • img: Path to the image to display as background.
  • bbox: List of 4 elements to delimit the boundaries of the final Plot. It must be similar the following list: [xmin, xmax, ymin, ymax]
fixed_xy_lim
bool
✓
 If set to True, the xlim and ylim will be fixed.
date_in_title
bool
✓
 If set to True, the ts vColumn will be displayed in the title section.
date_f
function
✓
 Function used to display the ts vColumn.
date_style_dict
dict
✓
 Style Dictionary used to display the ts vColumn when date_in_title = False.
interval
int
✓
 Number of ms between each update.
repeat
bool
✓
 If set to True, the animation will be repeated.
return_html
bool
✓
 If set to True and if using a Jupyter notebook, the HTML of the animation will be generated.
ax
Matplotlib axes object
✓
 The axes to plot on.
**style_kwds
any
✓
 Any optional parameter to pass to the Matplotlib functions.

Returns

animation : Matplotlib animation object

Example

In [46]:
from verticapy.datasets import *
pop_growth = load_pop_growth()
amazon = load_amazon()
commodities = load_commodities()
gapminder = load_gapminder()
In [47]:
# Bar Race
pop_growth.animated("year", ["city", "population"], "continent", 1970, 1980, "bar",)
Out[47]:
In [48]:
# Animated Pie
pop_growth.animated("year", ["city", "population"], "continent", 1970, 1980, "pie",)
Out[48]:
In [50]:
# Animated TS
commodities.animated("date", kind="ts",)
Out[50]:
In [51]:
# Animated Bubble
gapminder.animated("year", ["lifeExp", "gdpPercap", "country", "pop",], "continent", 
                   kind="bubble", limit_labels=10, limit_over=100,)
Out[51]: