Not including first rows of dataset, row shifting, incorrectly annotating row as left-hand labels, whereas labels on the right are correct

[rmaarle]

review_example.csv

import forestplot as fp
import pandas as pd

df = pd.read_csv("review_example.csv",sep=";") # companion example data


fp.forestplot(df, # the dataframe with results data
 estimate='PCSA_Men_mean', # col containing estimated effect size 
 ll= 'PCSA_Men_Lower', hl='PCSA_Men_Upper', # columns containing conf. int. lower and higher limits
 varlabel='Abbreviation', # column containing variable label
 capitalize="capitalize", # Capitalize labels
 annote=["Source", "Image modality", 'Sample_size',"Method", 'Position'], # columns to report on left of plot
 annoteheaders=["Ref", "Modality", 'N',"PCSA", 'Pose'], # ^corresponding headers
 rightannote=['Age', 'Height', 'Weight', 'Fiber_length', 'Pennation', "Info"], # columns to report on right of plot 
 right_annoteheaders=['Age[y]', 'Height[cm]', 'Weight[kg]', 'Fiber_length[cm]', 'Pennation[Deg]', "Note"], #corresponding headers
 
 groupvar= "Agegroup", # column containing group labels
 group_order=["Reference","Young Adults","Adults"], 
 xlabel="PCSA Ratio", # x-label title
 xticks=[0,30,60], # x-ticks to be printed
 table=True, # Format as a table
 color_alt_rows=True, # Gray alternate rows
 # Additional kwargs for customizations
 **{"marker": "D", # set maker symbol as diamond
 "markersize": 35, # adjust marker size
 "xtick_size": 12, # adjust x-ticker fontsize
 })
#plt.savefig("plot.jpg", bbox_inches="tight")

[rmaarle]

The example code with the sleep dataset worked perfectly, however when I implemented my own dataset various mistakes arose. I hope someone has a solution for this?

[LSYS]

hi @rmaarle, thanks for raising this. I wasn't aware that duplicated variable labels (varlabel) would create problems, which is likely the source of the problem. If you use some other unduplicated label, things should work as expected.

Minimal example:

import forestplot as fp
import pandas as pd

df = pd.read_csv("review_example.csv",sep=";") # companion example data
df = df.reset_index().astype({"index": str})

fp.forestplot(df, # the dataframe with results data
 estimate='PCSA_Men_mean', # col containing estimated effect size 
 ll= 'PCSA_Men_Lower', hl='PCSA_Men_Upper', # columns containing conf. int. lower and higher limits
 varlabel="index",
)

Your case (main change is varlabel=index):

import forestplot as fp
import pandas as pd

df = pd.read_csv("review_example.csv",sep=";") # companion example data
df = df.reset_index().astype({"index": str})

fp.forestplot(df, # the dataframe with results data
 estimate='PCSA_Men_mean', # col containing estimated effect size 
 ll= 'PCSA_Men_Lower', hl='PCSA_Men_Upper', # columns containing conf. int. lower and higher limits
 varlabel='index', # column containing variable label
 capitalize="capitalize", # Capitalize labels
 annote=["Source", "Image modality", 'Sample_size',"Method", 'Position'], # columns to report on left of plot
 annoteheaders=["Ref", "Modality", 'N',"PCSA", 'Pose'], # ^corresponding headers
 rightannote=['Age', 'Height', 'Weight', 'Fiber_length', 'Pennation',], # columns to report on right of plot 
 right_annoteheaders=['Age[y]', 'Height[cm]', 'Weight[kg]', 'Fiber_length[cm]', 'Pennation[Deg]'], #corresponding headers
 
 groupvar= "Agegroup", # column containing group labels
 group_order=["Reference","Young Adults","Adults"], 
 xlabel="PCSA Ratio", # x-label title
 xticks=[0,30,60], # x-ticks to be printed
 table=True, # Format as a table
 color_alt_rows=True, # Gray alternate rows
 # Additional kwargs for customizations
 **{"marker": "D", # set maker symbol as diamond
 "markersize": 35, # adjust marker size
 "xtick_size": 12, # adjust x-ticker fontsize
 }
)

[LSYS]

Your use case may find the future release (WIP) with grouped labels useful. The duplicated variable labels you were using were really groups. See #59 for an example.

[LSYS]

The next release will also warn about duplicated labels in the readme.