Seabornでヒートマップのサイズを大きくする
シーボーンでヒートマップを作成します
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)
ただし、問題は、データフレームに大量のデータがある場合、ヒートマップが小さすぎて、添付の画像のように内部の値が明確にならないことです。
ヒートマップのサイズをより大きく変更するにはどうすればよいですか？ありがとうございました - 
編集
私が試します：
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)
しかし、私はこのエラーを受け取ります：
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'
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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''
保持するwidth, heightパラメータを示すfigsizeを渡すことで、 Tuple を変更できます。
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)
編集
インデックスをTIMESTAMPとして設定する必要がある、あなたの同様の質問に答えたことを覚えています。したがって、次のようなことができます：
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)
投稿したデータフレームのheadの場合、プロットは次のようになります。
sns.heatmapの前にplt.figure(figsize=(16,5))を追加し、希望のサイズになるまでfigsize番号をいじります
...
plt.figure(figsize = (16,5))
ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5)