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How to bin data from multiple columns?
Selecting multiple columns in a pandas dataframeRenaming columns in pandasAdding new column to existing DataFrame in Python pandasHow to change the order of DataFrame columns?Delete column from pandas DataFrame“Large data” work flows using pandasChange data type of columns in PandasHow to iterate over rows in a DataFrame in Pandas?Select rows from a DataFrame based on values in a column in pandasGet list from pandas DataFrame column headers
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;
I have the following df
| 1 | 2 | 3 |
-------------------------
0.11 0.25 0.74
0.32 0.93 0.26
0.44 0.28 0.76
0.15 0.29 0.79
etc.
I'm using bins:
bins = [0,.1,.2,.3,.4,.5,.6,.7,.8,.9,1]
I created 3 bin columns and ran a value_counts() on them. So now I know how many values are in each bin for each of these 3 columns. But I'm having trouble plotting this into a barplot. Looking for a triple bar graph
df['Bin1'] = pd.cut(df['1'], bins)
df['Bin2'] = pd.cut(df['2'], bins)
df['Bin3'] = pd.cut(df['3'], bins)
Bin1_count = df['Bin1'].value_counts().values
Bin2_count = df['Bin2'].value_counts().values
Bin3_count = df['Bin3'].value_counts().values
x_axis = df['Bin1'].value_counts().index
sns.barplot(x = x_axis, y = [Bin1_count,Bin2_count,Bin3_count])
pandas bin
asked Mar 25 at 1:27
user10939484user10939484
646
add a comment |
I have the following df
| 1 | 2 | 3 |
-------------------------
0.11 0.25 0.74
0.32 0.93 0.26
0.44 0.28 0.76
0.15 0.29 0.79
etc.
I'm using bins:
bins = [0,.1,.2,.3,.4,.5,.6,.7,.8,.9,1]
I created 3 bin columns and ran a value_counts() on them. So now I know how many values are in each bin for each of these 3 columns. But I'm having trouble plotting this into a barplot. Looking for a triple bar graph
df['Bin1'] = pd.cut(df['1'], bins)
df['Bin2'] = pd.cut(df['2'], bins)
df['Bin3'] = pd.cut(df['3'], bins)
Bin1_count = df['Bin1'].value_counts().values
Bin2_count = df['Bin2'].value_counts().values
Bin3_count = df['Bin3'].value_counts().values
x_axis = df['Bin1'].value_counts().index
sns.barplot(x = x_axis, y = [Bin1_count,Bin2_count,Bin3_count])
pandas bin
asked Mar 25 at 1:27
user10939484user10939484
646
add a comment |
I have the following df
| 1 | 2 | 3 |
-------------------------
0.11 0.25 0.74
0.32 0.93 0.26
0.44 0.28 0.76
0.15 0.29 0.79
etc.
I'm using bins:
bins = [0,.1,.2,.3,.4,.5,.6,.7,.8,.9,1]
I created 3 bin columns and ran a value_counts() on them. So now I know how many values are in each bin for each of these 3 columns. But I'm having trouble plotting this into a barplot. Looking for a triple bar graph
df['Bin1'] = pd.cut(df['1'], bins)
df['Bin2'] = pd.cut(df['2'], bins)
df['Bin3'] = pd.cut(df['3'], bins)
Bin1_count = df['Bin1'].value_counts().values
Bin2_count = df['Bin2'].value_counts().values
Bin3_count = df['Bin3'].value_counts().values
x_axis = df['Bin1'].value_counts().index
sns.barplot(x = x_axis, y = [Bin1_count,Bin2_count,Bin3_count])
pandas bin
asked Mar 25 at 1:27
user10939484user10939484
646
I have the following df
| 1 | 2 | 3 |
-------------------------
0.11 0.25 0.74
0.32 0.93 0.26
0.44 0.28 0.76
0.15 0.29 0.79
etc.
I'm using bins:
bins = [0,.1,.2,.3,.4,.5,.6,.7,.8,.9,1]
I created 3 bin columns and ran a value_counts() on them. So now I know how many values are in each bin for each of these 3 columns. But I'm having trouble plotting this into a barplot. Looking for a triple bar graph
df['Bin1'] = pd.cut(df['1'], bins)
df['Bin2'] = pd.cut(df['2'], bins)
df['Bin3'] = pd.cut(df['3'], bins)
Bin1_count = df['Bin1'].value_counts().values
Bin2_count = df['Bin2'].value_counts().values
Bin3_count = df['Bin3'].value_counts().values
x_axis = df['Bin1'].value_counts().index
sns.barplot(x = x_axis, y = [Bin1_count,Bin2_count,Bin3_count])
pandas bin
pandas bin
asked Mar 25 at 1:27
user10939484user10939484
646
asked Mar 25 at 1:27
user10939484user10939484
646
asked Mar 25 at 1:27
user10939484user10939484
646
asked Mar 25 at 1:27
user10939484user10939484
646
asked Mar 25 at 1:27
user10939484user10939484
646
646
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
You can using melt first , then using pd.crosstab, and try look at plot from pandas
meltdf=df.melt()
meltdf.value=pd.cut(meltdf.value,bins)
pd.crosstab(meltdf.variable,meltdf.value).plot(kind='bar')
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 domeltdf=df[['1','2','3']].melt()
– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
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
You can using melt first , then using pd.crosstab, and try look at plot from pandas
meltdf=df.melt()
meltdf.value=pd.cut(meltdf.value,bins)
pd.crosstab(meltdf.variable,meltdf.value).plot(kind='bar')
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 domeltdf=df[['1','2','3']].melt()
– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
add a comment |
You can using melt first , then using pd.crosstab, and try look at plot from pandas
meltdf=df.melt()
meltdf.value=pd.cut(meltdf.value,bins)
pd.crosstab(meltdf.variable,meltdf.value).plot(kind='bar')
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 domeltdf=df[['1','2','3']].melt()
– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
add a comment |
You can using melt first , then using pd.crosstab, and try look at plot from pandas
meltdf=df.melt()
meltdf.value=pd.cut(meltdf.value,bins)
pd.crosstab(meltdf.variable,meltdf.value).plot(kind='bar')
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
You can using melt first , then using pd.crosstab, and try look at plot from pandas
meltdf=df.melt()
meltdf.value=pd.cut(meltdf.value,bins)
pd.crosstab(meltdf.variable,meltdf.value).plot(kind='bar')
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
answered Mar 25 at 1:55
WeNYoBenWeNYoBen
140k84878
140k84878
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 domeltdf=df[['1','2','3']].melt()
– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
add a comment |
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 domeltdf=df[['1','2','3']].melt()
– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
I also have other columns in the df of other types so I'm getting a "'<' not supported between instances of 'int' and 'str'" error
– user10939484
Mar 25 at 2:11
@user10939484 do
meltdf=df[['1','2','3']].melt()– WeNYoBen
Mar 25 at 2:18
@user10939484 do
meltdf=df[['1','2','3']].melt()– WeNYoBen
Mar 25 at 2:18
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
Nevermind, just made a separate dataframe of columns I needed. Thanks
– user10939484
Mar 25 at 2:19
add a comment |
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