Python - Changing the format of the bottom values to show the month
New to python and pandas, I got my function working correctly by looking for existing code however I want to change the bottom values from numbers to actual texts, which in this case would be months.
from sklearn.cluster import AgglomerativeClustering as AC
def scale_df(df,axis=0):
return (df - df.mean(axis=axis))/df.std(axis=axis)
colormap = sns.diverging_palette(220, 10, as_cmap=True)
def plot_hmap(df, ix=None, cmap=colormap):
if ix is None:
ix = np.arange(df.shape[0])
plt.imshow(df.iloc[ix,:], cmap=cmap)
plt.colorbar(fraction=0.03)
plt.yticks(np.arange(df.shape[0]), df.index[ix])
plt.xticks(np.arange(df.shape[1]))
plt.grid(False)
plt.show()
def scale_and_plot(df, ix=None):
df_marginal_scaled = scale_df(df.T).T
if ix is None:
ix = AC(4).fit(df_marginal_scaled).labels_.argsort() # a trick to make better heatmaps
cap = np.min([np.max(df_marginal_scaled.values), np.abs(np.min(df_marginal_scaled.values))])
df_marginal_scaled = np.clip(df_marginal_scaled, -1*cap, cap)
plot_hmap(df_marginal_scaled, ix=ix)
month_by_type = crimeDataMonth.pivot_table(values='Month', index='Crime type', columns=crimeDataMonth.index.month, aggfunc=np.size).fillna(0)
plt.figure(figsize=(15,12))
scale_and_plot(month_by_type)
My table is the following which has the month:
python pandas matplotlib seaborn
edited Nov 23 '18 at 20:07
Abhi
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
add a comment |
New to python and pandas, I got my function working correctly by looking for existing code however I want to change the bottom values from numbers to actual texts, which in this case would be months.
from sklearn.cluster import AgglomerativeClustering as AC
def scale_df(df,axis=0):
return (df - df.mean(axis=axis))/df.std(axis=axis)
colormap = sns.diverging_palette(220, 10, as_cmap=True)
def plot_hmap(df, ix=None, cmap=colormap):
if ix is None:
ix = np.arange(df.shape[0])
plt.imshow(df.iloc[ix,:], cmap=cmap)
plt.colorbar(fraction=0.03)
plt.yticks(np.arange(df.shape[0]), df.index[ix])
plt.xticks(np.arange(df.shape[1]))
plt.grid(False)
plt.show()
def scale_and_plot(df, ix=None):
df_marginal_scaled = scale_df(df.T).T
if ix is None:
ix = AC(4).fit(df_marginal_scaled).labels_.argsort() # a trick to make better heatmaps
cap = np.min([np.max(df_marginal_scaled.values), np.abs(np.min(df_marginal_scaled.values))])
df_marginal_scaled = np.clip(df_marginal_scaled, -1*cap, cap)
plot_hmap(df_marginal_scaled, ix=ix)
month_by_type = crimeDataMonth.pivot_table(values='Month', index='Crime type', columns=crimeDataMonth.index.month, aggfunc=np.size).fillna(0)
plt.figure(figsize=(15,12))
scale_and_plot(month_by_type)
My table is the following which has the month:
python pandas matplotlib seaborn
edited Nov 23 '18 at 20:07
Abhi
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
Can you share a sample ofmonth_by_typeinstead?
– yatu
Nov 23 '18 at 20:37
add a comment |
New to python and pandas, I got my function working correctly by looking for existing code however I want to change the bottom values from numbers to actual texts, which in this case would be months.
from sklearn.cluster import AgglomerativeClustering as AC
def scale_df(df,axis=0):
return (df - df.mean(axis=axis))/df.std(axis=axis)
colormap = sns.diverging_palette(220, 10, as_cmap=True)
def plot_hmap(df, ix=None, cmap=colormap):
if ix is None:
ix = np.arange(df.shape[0])
plt.imshow(df.iloc[ix,:], cmap=cmap)
plt.colorbar(fraction=0.03)
plt.yticks(np.arange(df.shape[0]), df.index[ix])
plt.xticks(np.arange(df.shape[1]))
plt.grid(False)
plt.show()
def scale_and_plot(df, ix=None):
df_marginal_scaled = scale_df(df.T).T
if ix is None:
ix = AC(4).fit(df_marginal_scaled).labels_.argsort() # a trick to make better heatmaps
cap = np.min([np.max(df_marginal_scaled.values), np.abs(np.min(df_marginal_scaled.values))])
df_marginal_scaled = np.clip(df_marginal_scaled, -1*cap, cap)
plot_hmap(df_marginal_scaled, ix=ix)
month_by_type = crimeDataMonth.pivot_table(values='Month', index='Crime type', columns=crimeDataMonth.index.month, aggfunc=np.size).fillna(0)
plt.figure(figsize=(15,12))
scale_and_plot(month_by_type)
My table is the following which has the month:
python pandas matplotlib seaborn
edited Nov 23 '18 at 20:07
Abhi
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
New to python and pandas, I got my function working correctly by looking for existing code however I want to change the bottom values from numbers to actual texts, which in this case would be months.
from sklearn.cluster import AgglomerativeClustering as AC
def scale_df(df,axis=0):
return (df - df.mean(axis=axis))/df.std(axis=axis)
colormap = sns.diverging_palette(220, 10, as_cmap=True)
def plot_hmap(df, ix=None, cmap=colormap):
if ix is None:
ix = np.arange(df.shape[0])
plt.imshow(df.iloc[ix,:], cmap=cmap)
plt.colorbar(fraction=0.03)
plt.yticks(np.arange(df.shape[0]), df.index[ix])
plt.xticks(np.arange(df.shape[1]))
plt.grid(False)
plt.show()
def scale_and_plot(df, ix=None):
df_marginal_scaled = scale_df(df.T).T
if ix is None:
ix = AC(4).fit(df_marginal_scaled).labels_.argsort() # a trick to make better heatmaps
cap = np.min([np.max(df_marginal_scaled.values), np.abs(np.min(df_marginal_scaled.values))])
df_marginal_scaled = np.clip(df_marginal_scaled, -1*cap, cap)
plot_hmap(df_marginal_scaled, ix=ix)
month_by_type = crimeDataMonth.pivot_table(values='Month', index='Crime type', columns=crimeDataMonth.index.month, aggfunc=np.size).fillna(0)
plt.figure(figsize=(15,12))
scale_and_plot(month_by_type)
My table is the following which has the month:
python pandas matplotlib seaborn
python pandas matplotlib seaborn
edited Nov 23 '18 at 20:07
Abhi
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
edited Nov 23 '18 at 20:07
Abhi
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
edited Nov 23 '18 at 20:07
Abhi
2,490320
edited Nov 23 '18 at 20:07
Abhi
2,490320
edited Nov 23 '18 at 20:07
Abhi
2,490320
2,490320
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
asked Nov 23 '18 at 19:50
Stuart AllenStuart Allen
132
132
Can you share a sample ofmonth_by_typeinstead?
– yatu
Nov 23 '18 at 20:37
add a comment |
Can you share a sample ofmonth_by_typeinstead?
– yatu
Nov 23 '18 at 20:37
Can you share a sample of
month_by_type instead?– yatu
Nov 23 '18 at 20:37
Can you share a sample of
month_by_type instead?– yatu
Nov 23 '18 at 20:37
add a comment |
1 Answer
1
active
oldest
votes
If i understand correctly, you would like to change the labels in the x-axis of the plot from the numbers [0, 1, ... 11]
to the names of the corresponding months ['January', 'February', ... 'December'].
If so, you could do that using this:
# Get the current locations of the labels
locations, labels = plt.xticks()
# Set the values of the new labels
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
# Place the new labels
plt.xticks(locations, labels=months)
You could do this with less hard-coded values using the calendar module:
import calendar
locations, labels = plt.xticks()
months = [calendar.month_name[n] for n in range(1, 13, 1)]
plt.xticks(locations, labels=months)
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
If i understand correctly, you would like to change the labels in the x-axis of the plot from the numbers [0, 1, ... 11]
to the names of the corresponding months ['January', 'February', ... 'December'].
If so, you could do that using this:
# Get the current locations of the labels
locations, labels = plt.xticks()
# Set the values of the new labels
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
# Place the new labels
plt.xticks(locations, labels=months)
You could do this with less hard-coded values using the calendar module:
import calendar
locations, labels = plt.xticks()
months = [calendar.month_name[n] for n in range(1, 13, 1)]
plt.xticks(locations, labels=months)
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
add a comment |
If i understand correctly, you would like to change the labels in the x-axis of the plot from the numbers [0, 1, ... 11]
to the names of the corresponding months ['January', 'February', ... 'December'].
If so, you could do that using this:
# Get the current locations of the labels
locations, labels = plt.xticks()
# Set the values of the new labels
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
# Place the new labels
plt.xticks(locations, labels=months)
You could do this with less hard-coded values using the calendar module:
import calendar
locations, labels = plt.xticks()
months = [calendar.month_name[n] for n in range(1, 13, 1)]
plt.xticks(locations, labels=months)
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
add a comment |
If i understand correctly, you would like to change the labels in the x-axis of the plot from the numbers [0, 1, ... 11]
to the names of the corresponding months ['January', 'February', ... 'December'].
If so, you could do that using this:
# Get the current locations of the labels
locations, labels = plt.xticks()
# Set the values of the new labels
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
# Place the new labels
plt.xticks(locations, labels=months)
You could do this with less hard-coded values using the calendar module:
import calendar
locations, labels = plt.xticks()
months = [calendar.month_name[n] for n in range(1, 13, 1)]
plt.xticks(locations, labels=months)
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
If i understand correctly, you would like to change the labels in the x-axis of the plot from the numbers [0, 1, ... 11]
to the names of the corresponding months ['January', 'February', ... 'December'].
If so, you could do that using this:
# Get the current locations of the labels
locations, labels = plt.xticks()
# Set the values of the new labels
months = ['January', 'February', 'March', 'April', 'May', 'June', 'July',
'August', 'September', 'October', 'November', 'December']
# Place the new labels
plt.xticks(locations, labels=months)
You could do this with less hard-coded values using the calendar module:
import calendar
locations, labels = plt.xticks()
months = [calendar.month_name[n] for n in range(1, 13, 1)]
plt.xticks(locations, labels=months)
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
edited Nov 23 '18 at 21:55
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
answered Nov 23 '18 at 21:44
Gal AvineriGal Avineri
16210
16210
add a comment |
add a comment |
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Can you share a sample of
month_by_typeinstead?– yatu
Nov 23 '18 at 20:37