In [1]:

import pandas as pd
import forestplot as fp
print(fp.__version__)

0.2.2

Table headers don't work as expected with 6 (or fewer) rows of data¶

See issue #52

In [2]:

df = fp.load_data("sleep")
df.head(3)

Out[2]:

	n	r	CI95%	p-val	BF10	power	var	hl	ll	moerror	group	label
0	706	0.090373	[0.02 0.16]	0.016309	0.839	0.67	age	0.16	0.02	0.069627	age	in years
1	706	0.048081	[-0.03 0.12]	0.201948	0.106	0.25	clerical	0.12	-0.03	0.071919	occupation	=1 if clerical worker
2	706	0.041229	[-0.03 0.11]	0.273948	0.086	0.19	construc	0.11	-0.03	0.068771	occupation	=1 if construction worker

In [3]:

std_opts = dict(
    estimate="r",
    ll="ll", hl="hl",
    varlabel="label",
    capitalize="capitalize",  
    pval="p-val",  # column containing p-values to be formatted
    annote=["n", "power", "est_ci"],  # columns to report on left of plot
    annoteheaders=["N", "Power", "Est. (95% Conf. Int.)"],  # ^corresponding headers
    rightannote=["formatted_pval", "group"],  # columns to report on right of plot 
    right_annoteheaders=["P-value", "Variable group"],  # ^corresponding headers
    xlabel="Pearson correlation coefficient",  # x-label title
    table=True
)

In [4]:

# 6 rows and below: Right annotation disappears
fp.forestplot(df.head(6), **std_opts)

Out[4]:

<AxesSubplot:xlabel='Pearson correlation coefficient'>

In [5]:

# 7 rows and above: Things work as expected
fp.forestplot(df.head(7), **std_opts)

Out[5]:

<AxesSubplot:xlabel='Pearson correlation coefficient'>

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