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### Answer rating: 297

### Answer rating: 123

How can one modify the format for the output from a groupby operation in pandas that produces scientific notation for very large numbers?

I know how to do string formatting in python but I"m at a loss when it comes to applying it here.

```
df1.groupby("dept")["data1"].sum()
dept
value1 1.192433e+08
value2 1.293066e+08
value3 1.077142e+08
```

This suppresses the scientific notation if I convert to string but now I"m just wondering how to string format and add decimals.

```
sum_sales_dept.astype(str)
```

Granted, the answer I linked in the comments is not very helpful. You can specify your own string converter like so.

```
In [25]: pd.set_option("display.float_format", lambda x: "%.3f" % x)
In [28]: Series(np.random.randn(3))*1000000000
Out[28]:
0 -757322420.605
1 -1436160588.997
2 -1235116117.064
dtype: float64
```

I"m not sure if that"s the preferred way to do this, but it works.

Converting numbers to strings purely for aesthetic purposes seems like a bad idea, but if you have a good reason, this is one way:

```
In [6]: Series(np.random.randn(3)).apply(lambda x: "%.3f" % x)
Out[6]:
0 0.026
1 -0.482
2 -0.694
dtype: object
```

Here is another way of doing it, similar to Dan Allan"s answer but without the lambda function:

```
>>> pd.options.display.float_format = "{:.2f}".format
>>> Series(np.random.randn(3))
0 0.41
1 0.99
2 0.10
```

or

```
>>> pd.set_option("display.float_format", "{:.2f}".format)
```

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