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added tutorial to visualize to data frame (#27973)

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Prasad Akmar
2018-12-17 22:09:24 -05:00
committed by Christopher McCormack
parent 4444ba2a8c
commit 669be64920
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guide/english/data-science-tools/pandas/index.md
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@ -26,7 +26,7 @@ df = pd.read_csv(file_path)
``` ```
Here, `file_path` can be a local path to a csv file on you computer, or an url pointing to one. The column names may be included in the csv file, or may be passed as an argument. For more on this, and much more, take a look at the [documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html?highlight=read_csv#pandas.read_csv). Here, `file_path` can be a local path to a csv file on you computer, or an url pointing to one. The column names may be included in the csv file, or may be passed as an argument. For more on this, and much more, take a look at the [documentation](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html?highlight=read_csv#pandas.read_csv).
## Getting an overview of a data frame ## Getting an Overview of a Data Frame
To show the first few rows of a data frame, the `head` method is useful (once more this should sound familiar to R programmers): To show the first few rows of a data frame, the `head` method is useful (once more this should sound familiar to R programmers):
```python ```python
df.head() df.head()
@ -82,6 +82,17 @@ Get the mean of the values for the requested axis
mean = df.mean() mean = df.mean()
``` ```
### Visualizing the Data in the Dataframe
To visualize the data in the dataframe, we can use matplotlib library. Here's how to use it:
The below code will setup matplotlib inline in your Jupyter notebook. set the style to be 'ggplot', one of the many styles available in matplotlib. and plot a histogram of a given ColumnName from the dataframe
```python
%matplotlib inline
import matplotlib
matplotlib.style.use('ggplot')
df['ColumnName'].plot.hist()
```
#### More Information: #### More Information:
1. [pandas](http://pandas.pydata.org/) 1. [pandas](http://pandas.pydata.org/)
2. [read_csv](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html?highlight=read_csv#pandas.read_csv) 2. [read_csv](http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html?highlight=read_csv#pandas.read_csv)