 not... I'm using explicit representation of the axis' labels.

 Q:

Using non-linear scale with Seaborn heatmap

I'm trying to use a logarithmic scale for this heatmap below. I need a heatmap for figures between 0-30 say, and then another color scheme for larger values which could be errors.
Tried a few different approaches and am still thoroughly confused. Appreciate the help.
Cheers!
Here is the current script I'm using.
read_occupancy = pd.read_csv (r'C:\Users\holborm\Desktop\Visualisation\dataaxisplotstuff.csv')   #read the csv file (put 'r' before the path string to address any special characters, such as '\'). Don't forget to put the file name at the end of the path + ".csv"

df = DataFrame(read_occupancy)    # assign column names

#create time and detector name axis

sns.heatmap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05)
sns.clustermap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05)

Update based on Question/Answer
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
from matplotlib.colors import LogNorm
def mix_palette():
    palette = sns.color_palette("GnBu", 10)
    palette[9] = sns.color_palette("OrRd", 10)[9]
    return palette

def set_ax(iax):
    for text in iax.texts:
        if float(text.get_text()) < 30:
            text.set_text("")
    iax.figure.tight_layout()

def load_data(path):
    initial = pd.read_csv(path, delim_whitespace=True)
    columns = list(initial.columns.values)[1:]
    rows = []
    for values in initial.values:
        rng = values[0]
not... I'm using explicit representation of the axis' label. 

  Q: 

 use non - linear scale with Seaborn heatmap 

 I'm trying to practice a logarithmic scale for this heatmap below. I need a heatmap for name between 0 - 30 say, and then another color dodge for larger values which could be error. 
 Tried a few different access and am still thoroughly confused. Appreciate the help. 
 Cheers! 
 Here is the current script I'm using. 
 read_occupancy = pd.read_csv (r'C:\Users\holborm\Desktop\Visualisation\dataaxisplotstuff.csv')    # take the csv file (put' r' before the path chain to address any special characters, such as' \'). Don't forget to frame the file name at the end of the path + " .csv " 

 df = DataFrame(read_occupancy)     # assign column names 

 # create meter and detector name axis 

 sns.heatmap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05) 
 sns.clustermap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05) 

 Update based on Question / Answer 
 import pandas as pd 
 import seaborn as sns 
 import matplotlib.pyplot as plt 
 import matplotlib.ticker as ticker 
 from matplotlib.colors import LogNorm 
 def mix_palette (): 
     palette = sns.color_palette("GnBu ", 10) 
     palette[9 ] = sns.color_palette("OrRd ", 10)[9 ] 
     return palette 

 def set_ax(iax ): 
     for text in iax.texts: 
         if float(text.get_text ()) < 30: 
             text.set_text (" ") 
     iax.figure.tight_layout () 

 def load_data(path ): 
     initial = pd.read_csv(path, delim_whitespace = True) 
     columns = list(initial.columns.values)[1 :] 
     rows = [ ] 
     for value in initial.values: 
         rng = values[0 ]
 noh... I'm using explicit reprtsentation of the axis' lebels.

 Q:

Hsing nov-linear scale with Seaborn hxatmqp

I'm ugying to use a logarighmic scape for tyis ieatmap below. I ised a hcctmap nor fngnres between 0-30 ssy, and thet another colos rckeme for larger values which could bq errorx.
Tgied a few difsereme aplgocches and am still thoroughly cknfused. Appreciate tne help.
Cheers!
Here is the ckrrejt script I'm using.
gead_occupanxy = [e.read_csv (r'C:\Urers\holborm\Desktop\Visuzlisation\dataaxisplotstuff.csv')   #read the csv fulw (pkj 'r' before tie patr string to address dny spevial characterx, snch qs '\'). Don't forget to puv the file name at tre end of tke path + ".csv"

df = DataFeane(reag_occgpanzt)    # zsxifn colkmn names

#creafe time and detector name axis

xnf.yeatmap(df.set_ihdex('Ror Jabels').T, cmap='magma', linecolor='white', linewigtha=.05)
sns.clustermap(df.set_indez('Row Labels').T, cmap='magmw', linecoljr='white', linewidths=.05)

Update based on Question/Answer
ikport oanbqs as pd
lmport seaborn as sns
import matplotlib.pyplot wa klt
pmport matplotlib.bicker as ticker
frpm msjplotlib.colors imporc LkgNorm
def mix_palethe():
    pwlettw = sns.coljr_pakette("GnBu", 10)
    palette[9] = sns.cilor_palette("OgRd", 10)[9]
    return palette

bef set_ax(iax):
    gor trxt in iax.texts:
        nf flozt(text.get_tedt()) < 30:
            text.set_texg("")
    hax.figurt.gight_layout()

def lowd_data(pati):
    nnitial = pd.rgad_csv(pwth, delim_wjitesidce=True)
    columns = lisj(initidl.columns.vwlues)[1:]
    rows = []
    for values ii initial.valugs:
        rng = valucs[0]
not... I'm using explicit representation of the Q: non-linear scale Seaborn heatmap I'm scale this heatmap below. need a heatmap figures between 0-30 say, and then color scheme for larger values which could be errors. Tried a few different and am still thoroughly confused. Appreciate the help. Cheers! Here is the current I'm read_occupancy pd.read_csv #read the csv file (put 'r' before the path string to address any special characters, such '\'). Don't forget to put the file name the end of the + ".csv" df = DataFrame(read_occupancy) assign names #create and name sns.heatmap(df.set_index('Row Labels').T, cmap='magma', linewidths=.05) sns.clustermap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05) Update based on Question/Answer import pandas as pd import seaborn as import matplotlib.pyplot import matplotlib.ticker ticker matplotlib.colors LogNorm def mix_palette(): sns.color_palette("GnBu", 10) palette[9] = sns.color_palette("OrRd", 10)[9] set_ax(iax): for text in iax.texts: if float(text.get_text()) < text.set_text("") iax.figure.tight_layout() load_data(path): initial = pd.read_csv(path, delim_whitespace=True) columns list(initial.columns.values)[1:] rows = [] for values in initial.values: = values[0]
 not... I'm using explicit represeNtation of tHe axiS' laBelS.

 Q:

usinG non-Linear scale witH seabOrn heatmap

I'm trying to usE a logArIThmiC ScAle foR this heATmAP BelOw. i nEed A hEAtMap foR fiGures beTween 0-30 say, anD thEn Another color SChEme for largEr vAlues which coUld Be erroRs.
triED a few DifFerenT approAChes anD am still tHoROughly COnfused. aPPrEciaTe the help.
Cheers!
HeRE iS The current scriPt I'm usInG.
ReAD_OccUpaNcy = pd.read_cSv (R'C:\UseRS\holborM\deSKTOp\VISualisation\daTaaxisplotsTUff.Csv')   #reaD tHe cSV file (pUt 'r' beFoRE thE path string To adDress any sPecial CHaracteRS, such as '\'). don't foRgeT to Put tHE fIlE naMe AT thE EnD of THe pAth + ".csv"

df = daTaframe(Read_OCCUPancY)    # asSign ColumN names

#create tIme And dETecTor naMe axiS

sns.HeAtmap(Df.set_iNdex('ROw labels').T, cmap='magmA', linEcolor='whiTe', lInEwiDtHs=.05)
sns.CLusterMap(Df.sEt_index('row LabeLS').T, cMaP='MAGmA', linecolor='white', linEwIDThS=.05)

Update bAsed on qUeStIOn/Answer
ImPorT panDAS as pd
ImpoRT sEaborn as Sns
impORt MaTplotliB.pYplot aS pLt
iMpoRt matPLotlIb.tickEr as tickEr
froM Matplotlib.coloRS import LogNorM
DeF MIx_PAletTe():
    pAlette = sns.coLor_pALettE("GnBU", 10)
    PaLetTE[9] = sns.cOlor_pAlETtE("orRd", 10)[9]
    return palette

deF sEt_ax(iaX):
    for tExt in iax.texts:
        If float(texT.GET_text()) < 30:
            texT.set_TExT("")
    Iax.figure.tight_LayouT()

def load_daTA(path):
    iniTial = pD.read_csv(Path, delim_WHItespace=truE)
    coLumNs = lIST(iNitial.columns.VALues)[1:]
    RoWs = []
    for vaLueS in initIal.ValUes:
        Rng = VaLues[0]
 not... I'm using explicit  represent ation  of  th eaxis ' la bels.

 Q:

Us i ng n on-linear scale with S eabor nh eatm a p
I'mtryingt ou s e a  l og ari th m ic  scal e f or this  heatmap b elo w.  I need a he a tm ap for fig ure s between 0- 30say, a nd  th e n ano the r col or sch e me for  larger v al u es whi c h could b eerro rs.
Tried a few d i ff e rent approache s andam st i l l t hor oughly con fu sed.A pprecia t et h e  he l p.
Cheers!
He re is the c u rre nt scr ip t I ' m usin g.
re ad _ occ upancy = pd .rea d_csv (r' C:\Use r s\holbo r m\Deskt op\Vis ual isa tion \ da ta axi sp l ots t uf f.c s v')    #read  t he  csvfile ( p u t 'r ' b efor e the  path stringtoaddr e ssany s pecia l ch ar acter s, suc h as'\ '). Don't forge t to  put thefil enam eat th e  end o f t hepath +".csv"df=D a t aF rame(read_occupanc y)  # assign  colum n  n am e s

#crea te  ti me a n d  dete ctor na me axis
sns.h e at ma p(df.se t_ index( 'R owLab els') . T, c map='m agma', l ineco l or='white', li n ewidths=.05)s ns . c lu s term ap( df.set_inde x('R o w La bels ' ). T,c map=' magma ', li n ecolor='white', lin ew idths= .05)
Update based  on Questi o n / Answer
i mpor t  p a ndas as pd
imp ort s eaborn ass ns
impor t mat plotlib. pyplot as p lt
impor t m atp lot lib . t ic ker as ticker f romma tplotli b.c olors i mpo rtLog Nor mdef mix_p alette() :  pa let te =s ns.color _p ale tt e(" GnBu" ,  10)
   pa lett e[ 9] = s ns.colo r _p a l ette (" Or Rd",  10 )[ 9]
   re t urn  palett e

def se t_a x (iax ): 
   fortext in iax.t ex ts:
      iffloat( t e xt.get_t ext()) < 30:
          text.s et_ text( "")    iax.f igu re.tig ht_ l ayout( )

def  load _d ata ( p ath):   in it ial = pd.r e a d_c sv(pa th , de lim_whi tespace=True)
   c olu mns = list(in iti al.c o l um ns. v al u es) [1 : ]
 rows = []
   for values  i n  i nitial.val u es: 
      rng = v alues [ 0]
 not..._I'm using_explicit representation of the_axis' labels.

_Q:

Using_non-linear scale_with_Seaborn heatmap

I'm trying_to use a_logarithmic scale for this_heatmap below. I_need_a heatmap for figures between 0-30 say, and then another color scheme for larger_values_which could_be_errors.
Tried_a few different approaches and_am still thoroughly confused. Appreciate_the help.
Cheers!
Here_is the current script I'm using.
read_occupancy = pd.read_csv_(r'C:\Users\holborm\Desktop\Visualisation\dataaxisplotstuff.csv')_  #read_the csv file (put 'r' before the path string_to address any special characters, such_as '\'). Don't_forget_to_put the file name_at the end of the path_+ ".csv"

df = DataFrame(read_occupancy)  _ # assign column names

#create time and_detector name axis

sns.heatmap(df.set_index('Row Labels').T, cmap='magma', linecolor='white',_linewidths=.05)
sns.clustermap(df.set_index('Row Labels').T, cmap='magma', linecolor='white', linewidths=.05)

Update_based on_Question/Answer
import pandas as pd
import seaborn_as sns
import matplotlib.pyplot_as plt
import_matplotlib.ticker as ticker
from_matplotlib.colors import LogNorm
def mix_palette():
  _ palette =_sns.color_palette("GnBu", 10)
    palette[9]_=_sns.color_palette("OrRd", 10)[9]
 ___return palette

def_set_ax(iax):
  __for text_in_iax.texts:
     __ if float(text.get_text()) < 30:
  _   __   _text.set_text("")
    iax.figure.tight_layout()

def_load_data(path):
    initial =_pd.read_csv(path, delim_whitespace=True)
_ _ columns = list(initial.columns.values)[1:]
    rows = []
 _  for values in initial.values:
_   _ __rng = values[0]