I'm struggling with tables for matplotlib (blume). The table is for an automation project that will produce 22 different maps. The code below produce a table with 49 rows. Some figures will only have 6 rows. When the number of rows exceeds 25 I would like to use two columns.
import pandas as pd
import matplotlib.pyplot as plt
from blume.table import table
# Dataframe
df=pd.DataFrame({'nr': [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
'KnNamn': ['Härryda', 'Partille', 'Öckerö', 'Stenungsund', 'Tjörn', 'Orust',
'Sotenäs', 'Munkedal', 'Tanum', 'Dals-Ed', 'Färgelanda', 'Ale',
'Lerum', 'Vårgårda', 'Bollebygd', 'Grästorp', 'Essunga',
'Karlsborg', 'Gullspång', 'Tranemo', 'Bengtsfors', 'Mellerud',
'Lilla Edet', 'Mark', 'Svenljunga', 'Herrljunga', 'Vara', 'Götene',
'Tibro', 'Töreboda', 'Göteborg', 'Mölndal', 'Kungälv', 'Lysekil',
'Uddevalla', 'Strömstad', 'Vänersborg', 'Trollhättan', 'Alingsås',
'Borås', 'Ulricehamn', 'Åmål', 'Mariestad', 'Lidköping', 'Skara',
'Skövde', 'Hjo', 'Tidaholm', 'Falköping'],
'rel': [0.03650425, 0.05022105, 0.03009109, 0.03966735, 0.02793296,
0.03690838, 0.04757161, 0.05607283, 0.0546372 , 0.05452821,
0.06640368, 0.04252673, 0.03677577, 0.05385784, 0.0407173 ,
0.04024881, 0.05613226, 0.04476127, 0.08543165, 0.04070175,
0.09281077, 0.08711656, 0.06111578, 0.04564958, 0.05058988,
0.04618078, 0.04640402, 0.04826498, 0.08514253, 0.07799246,
0.07829886, 0.04249149, 0.03909206, 0.06835601, 0.08027622,
0.07087295, 0.09013876, 0.1040369 , 0.05004451, 0.06584845,
0.04338739, 0.10570863, 0.0553109 , 0.05024871, 0.06531729,
0.05565605, 0.05041816, 0.04885198, 0.07954831]})
# Table
fig,ax = plt.subplots(1, figsize=(10, 7))
val =[]
ax.axis('off')
for i, j, k in zip(df.nr, df.KnNamn, df.rel):
k = k*100
k = round(k,2)
k= (str(k) ' %')
temp=str(i) '. ' str(j) ': ' str(k)
val.append(temp)
val=[[el] for el in val]
#val=val[0] val[1]
tab=table(ax,cellText=val,
#rowLabels=row_lab,
colLabels=['Relativ arbetslöshet'], loc='left', colWidths=[0.3], cellLoc='left')
plt.show()
As I understands it, if I want a table with two columns, my val object should be structured in a different way. In the case above, val is a nested list with 49 lists inside. I need to merge lists, I figure. I tried this pairwise for loop but that didn't work with range?
I'm sure there is a simple solution to this problem I have. Help would be much appreciated.
for i, j in zip(range(len(val)), range(len(val))[1:] range(len(val))[:1]):
print(i, j)
CodePudding user response：
I don't know if it is what you need but you could use zip() or better itertools.zip_longest() with val[:25], val[25:]
two_columns = []
for col1, col2 in itertools.zip_longest(values[:25], values[25:], fillvalue=''):
#print(f'{col1:25} | {col2}')
two_columns.append([col1, col2])
Full working example
import pandas as pd
import matplotlib.pyplot as plt
from blume.table import table
import itertools
df = pd.DataFrame({
'nr': [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49
],
'KnNamn': [
'Härryda', 'Partille', 'Öckerö', 'Stenungsund', 'Tjörn', 'Orust',
'Sotenäs', 'Munkedal', 'Tanum', 'Dals-Ed', 'Färgelanda', 'Ale',
'Lerum', 'Vårgårda', 'Bollebygd', 'Grästorp', 'Essunga',
'Karlsborg', 'Gullspång', 'Tranemo', 'Bengtsfors', 'Mellerud',
'Lilla Edet', 'Mark', 'Svenljunga', 'Herrljunga', 'Vara', 'Götene',
'Tibro', 'Töreboda', 'Göteborg', 'Mölndal', 'Kungälv', 'Lysekil',
'Uddevalla', 'Strömstad', 'Vänersborg', 'Trollhättan', 'Alingsås',
'Borås', 'Ulricehamn', 'Åmål', 'Mariestad', 'Lidköping', 'Skara',
'Skövde', 'Hjo', 'Tidaholm', 'Falköping'
],
'rel': [
0.03650425, 0.05022105, 0.03009109, 0.03966735, 0.02793296,
0.03690838, 0.04757161, 0.05607283, 0.0546372 , 0.05452821,
0.06640368, 0.04252673, 0.03677577, 0.05385784, 0.0407173 ,
0.04024881, 0.05613226, 0.04476127, 0.08543165, 0.04070175,
0.09281077, 0.08711656, 0.06111578, 0.04564958, 0.05058988,
0.04618078, 0.04640402, 0.04826498, 0.08514253, 0.07799246,
0.07829886, 0.04249149, 0.03909206, 0.06835601, 0.08027622,
0.07087295, 0.09013876, 0.1040369 , 0.05004451, 0.06584845,
0.04338739, 0.10570863, 0.0553109 , 0.05024871, 0.06531729,
0.05565605, 0.05041816, 0.04885198, 0.07954831
]
})
# df = df[:25] # test for 25 rows
# ---
fig, ax = plt.subplots(1, figsize=(10, 7))
ax.axis('off')
# --- values ---
#values = []
#for number, name, rel in zip(df.nr, df.KnNamn, df.rel):
# text = f'{number}. {name}: {rel*100:.2} %'
# values.append(text)
values = df.apply(lambda row: f'{row["nr"]}. {row["KnNamn"]}: {row["rel"]*100:.2} %', axis=1).values
# --- columns ---
if len(values) > 25:
two_columns = []
for col1, col2 in itertools.zip_longest(values[:25], values[25:], fillvalue=''):
#print(f'{col1:25} | {col2}')
two_columns.append([col1, col2])
tab = table(ax, cellText=two_columns,
#rowLabels=row_lab,
colLabels=['Col1', 'Col2'], colWidths=[0.3, 0.3], loc=-100, cellLoc='left')
else:
one_column = [[item] for item in values]
tab = table(ax, cellText=one_column,
#rowLabels=row_lab,
colLabels=['Col1'], colWidths=[0.3], loc=-100, cellLoc='left')
# --- plot ---
plt.show()
Result:
EDIT:
More universal version which can create many columns.
Example automatically create 3 columns for ROWS = 20.
import pandas as pd
import matplotlib.pyplot as plt
from blume.table import table
import itertools
df = pd.DataFrame({
'nr': [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49
],
'KnNamn': [
'Härryda', 'Partille', 'Öckerö', 'Stenungsund', 'Tjörn', 'Orust',
'Sotenäs', 'Munkedal', 'Tanum', 'Dals-Ed', 'Färgelanda', 'Ale',
'Lerum', 'Vårgårda', 'Bollebygd', 'Grästorp', 'Essunga',
'Karlsborg', 'Gullspång', 'Tranemo', 'Bengtsfors', 'Mellerud',
'Lilla Edet', 'Mark', 'Svenljunga', 'Herrljunga', 'Vara', 'Götene',
'Tibro', 'Töreboda', 'Göteborg', 'Mölndal', 'Kungälv', 'Lysekil',
'Uddevalla', 'Strömstad', 'Vänersborg', 'Trollhättan', 'Alingsås',
'Borås', 'Ulricehamn', 'Åmål', 'Mariestad', 'Lidköping', 'Skara',
'Skövde', 'Hjo', 'Tidaholm', 'Falköping'
],
'rel': [
0.03650425, 0.05022105, 0.03009109, 0.03966735, 0.02793296,
0.03690838, 0.04757161, 0.05607283, 0.0546372 , 0.05452821,
0.06640368, 0.04252673, 0.03677577, 0.05385784, 0.0407173 ,
0.04024881, 0.05613226, 0.04476127, 0.08543165, 0.04070175,
0.09281077, 0.08711656, 0.06111578, 0.04564958, 0.05058988,
0.04618078, 0.04640402, 0.04826498, 0.08514253, 0.07799246,
0.07829886, 0.04249149, 0.03909206, 0.06835601, 0.08027622,
0.07087295, 0.09013876, 0.1040369 , 0.05004451, 0.06584845,
0.04338739, 0.10570863, 0.0553109 , 0.05024871, 0.06531729,
0.05565605, 0.05041816, 0.04885198, 0.07954831
]
})
#df = df[:25] # test for 25 rows
# ---
fig, ax = plt.subplots(1, figsize=(10, 7))
ax.axis('off')
# --- values ---
def convert(row):
return f'{row["nr"]}. {row["KnNamn"]}: {row["rel"]*100:.2} %'
values = df.apply(convert, axis=1).values
# --- columns ---
ROWS = 20
#ROWS = 25
columns = []
for idx in range(0, len(values), ROWS):
columns.append(values[idx:idx ROWS])
columns_widths = [0.3] * len(columns)
columns_labels = [f'Col{i}' for i in range(1, len(columns) 1)]
rows = list(itertools.zip_longest(*columns, fillvalue=''))
# --- plot ---
tab = table(ax,
cellText=rows,
#rowLabels=row_lab,
colLabels=columns_labels,
colWidths=columns_widths,
loc=-100,
cellLoc='left')
plt.show()
Result:
