Bądź wielkości mapę cieplną większego z Seaborn

Question

utworzyć mapę cieplną z Seaborn

df1.index = pd.to_datetime(df1.index) 
df1 = df1.set_index('TIMESTAMP') 
df1 = df1.resample('30min').mean() 
ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5) 

Ale probleme jest, gdy istnieje wiele danych w dataframe termiczna będzie zbyt mały, a wartość wewnątrz nie rozpocznie jasne jak na załączonym obrazie.

Jak zmienić rozmiar mapy termicznej, aby była większa? Dziękuję

EDIT

Staram:

df1.index = pd.to_datetime(df1.index) 
fig, ax = plt.subplots(figsize=(10,10))   # Sample figsize in inches 
sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5, ax=ax) 
df1 = df1.set_index('TIMESTAMP') 
df1 = df1.resample('1d').mean() 
ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5) 

Ale otrzymuję ten błąd:

KeyError         Traceback (most recent call last) 
C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance) 
    1944    try: 
-> 1945     return self._engine.get_loc(key) 
    1946    except KeyError: 

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)() 

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)() 

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12368)() 

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)() 

KeyError: 'TIMESTAMP' 

During handling of the above exception, another exception occurred: 

KeyError         Traceback (most recent call last) 
<ipython-input-779-acaf05718dd8> in <module>() 
     2 fig, ax = plt.subplots(figsize=(10,10))   # Sample figsize in inches 
     3 sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5, ax=ax) 
----> 4 df1 = df1.set_index('TIMESTAMP') 
     5 df1 = df1.resample('1d').mean() 
     6 ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5) 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\frame.py in set_index(self, keys, drop, append, inplace, verify_integrity) 
    2835     names.append(None) 
    2836    else: 
-> 2837     level = frame[col]._values 
    2838     names.append(col) 
    2839     if drop: 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\frame.py in __getitem__(self, key) 
    1995    return self._getitem_multilevel(key) 
    1996   else: 
-> 1997    return self._getitem_column(key) 
    1998 
    1999  def _getitem_column(self, key): 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\frame.py in _getitem_column(self, key) 
    2002   # get column 
    2003   if self.columns.is_unique: 
-> 2004    return self._get_item_cache(key) 
    2005 
    2006   # duplicate columns & possible reduce dimensionality 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\generic.py in _get_item_cache(self, item) 
    1348   res = cache.get(item) 
    1349   if res is None: 
-> 1350    values = self._data.get(item) 
    1351    res = self._box_item_values(item, values) 
    1352    cache[item] = res 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\core\internals.py in get(self, item, fastpath) 
    3288 
    3289    if not isnull(item): 
-> 3290     loc = self.items.get_loc(item) 
    3291    else: 
    3292     indexer = np.arange(len(self.items))[isnull(self.items)] 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\pandas\indexes\base.py in get_loc(self, key, method, tolerance) 
    1945     return self._engine.get_loc(key) 
    1946    except KeyError: 
-> 1947     return self._engine.get_loc(self._maybe_cast_indexer(key)) 
    1948 
    1949   indexer = self.get_indexer([key], method=method, tolerance=tolerance) 

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4154)() 

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:4018)() 

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12368)() 

pandas\hashtable.pyx in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:12322)() 

KeyError: 'TIMESTAMP' 

EDIT

TypeError         Traceback (most recent call last) 
<ipython-input-890-86bff697504a> in <module>() 
     2 df2.resample('30min').mean() 
     3 fig, ax = plt.subplots() 
----> 4 ax = sns.heatmap(df2.iloc[:, 1:6:], annot=True, linewidths=.5) 
     5 ax.set_yticklabels([i.strftime("%Y-%m-%d %H:%M:%S") for i in df2.index], rotation=0) 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\seaborn\matrix.py in heatmap(data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, linewidths, linecolor, cbar, cbar_kws, cbar_ax, square, ax, xticklabels, yticklabels, mask, **kwargs) 
    483  plotter = _HeatMapper(data, vmin, vmax, cmap, center, robust, annot, fmt, 
    484       annot_kws, cbar, cbar_kws, xticklabels, 
--> 485       yticklabels, mask) 
    486 
    487  # Add the pcolormesh kwargs here 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\seaborn\matrix.py in __init__(self, data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, cbar, cbar_kws, xticklabels, yticklabels, mask) 
    165   # Determine good default values for the colormapping 
    166   self._determine_cmap_params(plot_data, vmin, vmax, 
--> 167          cmap, center, robust) 
    168 
    169   # Sort out the annotations 

C:\Users\Demonstrator\Anaconda3\lib\site-packages\seaborn\matrix.py in _determine_cmap_params(self, plot_data, vmin, vmax, cmap, center, robust) 
    202        cmap, center, robust): 
    203   """Use some heuristics to set good defaults for colorbar and range.""" 
--> 204   calc_data = plot_data.data[~np.isnan(plot_data.data)] 
    205   if vmin is None: 
    206    vmin = np.percentile(calc_data, 2) if robust else calc_data.min() 

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe'' 

Answer 1

Można zmienić figsize, przekazując tuple, pokazując parametry, które chcesz zachować.

import matplotlib.pyplot as plt 

fig, ax = plt.subplots(figsize=(10,10))   # Sample figsize in inches 
sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5, ax=ax) 

EDIT

Pamiętam, odpowiadając na podobne pytanie twój gdzie trzeba było ustawić indeks jako TIMESTAMP. Tak więc, można wtedy zrobić coś jak poniżej:

df = df.set_index('TIMESTAMP') 
df.resample('30min').mean() 
fig, ax = plt.subplots() 
ax = sns.heatmap(df.iloc[:, 1:6:], annot=True, linewidths=.5) 
ax.set_yticklabels([i.strftime("%Y-%m-%d %H:%M:%S") for i in df.index], rotation=0) 

Dla head z dataframe pan pisał, fabuła będzie wyglądać następująco:

Answer 2

fmt: string, opcjonalnie Kod formatowania ciągów znaków używany przy dodawaniu adnotacji

Pochodzenie: Seaborn docs

Dodaj parametr FMT z d, aby pokazać ją jako liczbę całkowitą

ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5, fmt="d") 

Answer 3

dodać plt.figure(figsize=(16,5)) przed sns.heatmap i bawić z numerami figsize aż pojawi się żądany rozmiar

... 

plt.figure(figsize = (16,5)) 

ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5)