Skip to content

Commit 4f24052

Browse files
plestrangemaxim-belkin
authored andcommitted
02-starting-with-data.md: fix typos
1. Typo: my ~> may 2. Missing space between sentences. Pull Request: #303
1 parent d1a46f2 commit 4f24052

1 file changed

Lines changed: 2 additions & 2 deletions

File tree

_episodes/02-starting-with-data.md

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -119,7 +119,7 @@ time we call a Pandas function.
119119

120120
# Reading CSV Data Using Pandas
121121

122-
We will begin by locating and reading our survey data which are in CSV format. CSV stands for Comma-Separated Values and is a common way store formatted data. Other symbols my also be used, so you might see tab-separated, colon-separated or space separated files. It is quite easy to replace one separator with another, to match your application. The first line in the file often has headers to explain what is in each column. CSV (and other separators) make it easy to share data, and can be imported and exported from many applications, including Microsoft Excel. For more details on CSV files, see the [Data Organisation in Spreadsheets](http://www.datacarpentry.org/spreadsheet-ecology-lesson/05-exporting-data/) lesson.
122+
We will begin by locating and reading our survey data which are in CSV format. CSV stands for Comma-Separated Values and is a common way store formatted data. Other symbols may also be used, so you might see tab-separated, colon-separated or space separated files. It is quite easy to replace one separator with another, to match your application. The first line in the file often has headers to explain what is in each column. CSV (and other separators) make it easy to share data, and can be imported and exported from many applications, including Microsoft Excel. For more details on CSV files, see the [Data Organisation in Spreadsheets](http://www.datacarpentry.org/spreadsheet-ecology-lesson/05-exporting-data/) lesson.
123123
We can use Pandas' `read_csv` function to pull the file directly into a
124124
[DataFrame](http://pandas.pydata.org/pandas-docs/stable/dsintro.html#dataframe).
125125

@@ -161,7 +161,7 @@ We can see that there were 35,549 rows parsed. Each row has 9
161161
columns. The first column is the index of the DataFrame. The index is used to
162162
identify the position of the data, but it is not an actual column of the DataFrame.
163163
It looks like the `read_csv` function in Pandas read our file properly. However,
164-
we haven't saved any data to memory so we can work with it.We need to assign the
164+
we haven't saved any data to memory so we can work with it. We need to assign the
165165
DataFrame to a variable. Remember that a variable is a name for a value, such as `x`,
166166
or `data`. We can create a new object with a variable name by assigning a value to it using `=`.
167167

0 commit comments

Comments
 (0)