使用 seaborn 使热图的大小更大
Make the size of a heatmap bigger with seaborn
我用 seaborn 创建了一个热图
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)
但问题是当数据帧中有大量数据时，热图会太小并且内部的值开始不清晰，如附图所示。
如何将热图的大小更改为更大？
谢谢
编辑
我试试：
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)
但是我得到这个错误：
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'
编辑
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''
您可以通过传递显示您希望保留的 width, height 参数的 tuple 来更改 figsize。
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)
编辑
我记得回答过您的一个类似问题，您必须将索引设置为 TIMESTAMP。因此，您可以执行如下操作：
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)
对于您发布的数据框的 head，绘图如下所示：
在 sns.heatmap 之前添加 plt.figure(figsize=(16,5)) 并尝试使用无花果大小的数字，直到获得所需的数字尺寸
...
plt.figure(figsize = (16,5))
ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5)
我不知道如何使用代码解决这个问题，但我手动调整了绘图右下角的控制面板，并调整了图形大小，如：
f, ax = plt.subplots(figsize=(16, 12))
在此期间，直到您获得匹配尺寸的彩色条。这对我有用。
我用 seaborn 创建了一个热图
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)
但问题是当数据帧中有大量数据时，热图会太小并且内部的值开始不清晰，如附图所示。
如何将热图的大小更改为更大？
谢谢
编辑
我试试：
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)
但是我得到这个错误：
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'
编辑
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''
您可以通过传递显示您希望保留的 width, height 参数的 tuple 来更改 figsize。
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)
编辑
我记得回答过您的一个类似问题，您必须将索引设置为 TIMESTAMP。因此，您可以执行如下操作：
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)
对于您发布的数据框的 head，绘图如下所示：
在 sns.heatmap 之前添加 plt.figure(figsize=(16,5)) 并尝试使用无花果大小的数字，直到获得所需的数字尺寸
...
plt.figure(figsize = (16,5))
ax = sns.heatmap(df1.iloc[:, 1:6:], annot=True, linewidths=.5)
我不知道如何使用代码解决这个问题，但我手动调整了绘图右下角的控制面板，并调整了图形大小，如：
f, ax = plt.subplots(figsize=(16, 12))
在此期间，直到您获得匹配尺寸的彩色条。这对我有用。