def main():
args = get_args(__file__)
labels = [
'N/A', 'Id. Física', 'Id. Historiográfica', 'Desconocido', 'Perdido'
]
colornames = ['light grey', 'medium green', 'denim blue', 'pale red']
df = pd.DataFrame(read_table(args.table))
df['ident'] = df.apply(categorize, axis=1)
data = df\
.drop_duplicates(['bid', 'lid'], keep='first')\
.pivot(index='bid', columns='lid', values='ident')\
.fillna(0)
#colors = sns.color_palette('hls', len(data))
#colors = sns.color_palette('husl', len(data))
#colors = sns.light_palette('red', len(data))
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Libros')
legend(f, ax, labels, colors)
plotting(plt, args)
def plot(args):
df = pd.DataFrame(read_table(args.table))
configurer = configs[args.color_by]
data, labels, colors = configurer(df, args.color_by)
f, ax = plt.subplots()
fig = sns.heatmap(
data,
ax=ax,
#square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), ylabel='Posición')
legend(f, ax, labels, colors)
if args.annotated and args.color_by in ['bid', 'year']:
df_by_bid = df.drop_duplicates('bid').set_index('bid')
texts = [
fig.text(
15,
bid,
df.loc[bid, 'short'],
fontsize=8,
) for bid, row in data.iterrows()
]
plotting(plt, args)
def main():
args = get_args(__file__)
df = pd.DataFrame(read_table(args.table))
def track(row):
# Mark it as id, which will go in red
return 1000 if row['bid'] == 25 else row['bid']
df['track'] = df.apply(track, axis=1)
data = df.pivot(index='pos', columns='lid', values='track')
colornames = ['light blue', 'bright red']
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Posición')
plotting(plt, args)
def main():
args = get_args(__file__)
df = pd.DataFrame(read_table(args.table))
data = df.pivot(index='pos', columns='lid', values='bid')
# colors = sns.color_palette('hls', len(data))
# colors = sns.color_palette('husl', len(data))
# colors = sns.light_palette('red', len(data))
colors = sns.light_palette('navy', len(data))
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Posición')
plotting(plt, args)
def main():
args = get_args(__file__)
names = ['NA', 'LAT', 'ROM', 'FRAN']
labels = ['N/A', 'Latín', 'Romance', 'Francés']
colornames = ['light grey', 'pale red', 'medium green', 'denim blue']
df = pd.DataFrame(read_table(args.table))
data = categorical_by(df, 'lang', names)
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Libros')
legend(f, ax, labels, colors)
plotting(plt, args)
def main():
args = get_args(__file__)
names = ['NA', 'REL', 'CRONIC', 'ANTI']
labels = ['N/A', 'Religioso', 'Crónicas y Leyes', 'Historia Antigua']
colornames = ['light grey', 'pale red', 'medium green', 'denim blue']
df = pd.DataFrame(read_table(args.table))
#df = pd.read_csv(args.table)
data = categorical_by(df, 'topic', names)
colors = sns.xkcd_palette(colornames)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(df.year.values), ylabel='Posición')
legend(f, ax, labels, colors)
plotting(plt, args)
def main():
args = get_args(__file__)
df = pd.DataFrame(read_table(args.table))
sizes = len(range(int(df['height'].max())))
data = df.pivot(index='pos', columns='lid', values='height').fillna(0)
#colors = sns.color_palette('cubehelix', sizes)
#colors = sns.color_palette('hls', len(data))
#colors = sns.color_palette('husl', len(data))
#colors = sns.light_palette('red', sizes)
#colors = sns.light_palette('navy', sizes)
colors = sns.light_palette('green', sizes)
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Tamaño')
plotting(plt, args)
def main():
args = get_args(__file__)
df = pd.DataFrame(read_table(args.table))
data = df\
.drop_duplicates(['bid', 'lid'], keep='first')\
.pivot(index='bid', columns='lid', values='year')\
.fillna(False)
#colors = sns.color_palette('hls', len(data))
#colors = sns.color_palette('husl', len(data))
colors = sns.light_palette('red', len(data))
f, ax = plt.subplots()
sns.heatmap(data,
ax=ax,
square=True,
linewidth=0.5,
cmap=ListedColormap(colors),
cbar=False)
set_axis(ax, data, as_letters(set(df.year.values)), 'Libros')
plotting(plt, args)